System And Method For Empirical-test-based Estimation Of Overall Thermal Performance Of A  Building With The Aid Of A Digital Computer

ABSTRACT

The overall thermal performance of a building UATotal can be empirically estimated through a short-duration controlled test. Preferably, the controlled test is performed at night during the winter. A heating source, such as a furnace, is turned off after the indoor temperature has stabilized. After an extended period, such as 12 hours, the heating source is briefly turned back on, such as for an hour, then turned off. The indoor temperature is allowed to stabilize. The energy consumed within the building during the test period is assumed to equal internal heat gains. Overall thermal performance is estimated by balancing the heat gained with the heat lost during the test period.

CROSS-REFERENCE TO RELATED APPLICATIONS

This non-provisional patent application is a continuation of U.S. patentapplication Ser. No. 14/294,087, filed Jun. 2, 2014, pending; whichclaims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patentapplication Ser. No. 61/935,285, filed Feb. 3, 2014, the disclosures ofwhich are incorporated by reference.

FIELD

This application relates in general to energy conservation and planningand, in particular, to a system and method for empirical-test-basedestimation of overall thermal performance of a building.

BACKGROUND

Concern has been growing in recent days over energy consumption in theUnited States and abroad. The cost of energy has steadily risen as powerutilities try to cope with continually growing demand, increasing fuelprices, and stricter regulatory mandates. Power utilities must alsomaintain existing infrastructure, while simultaneously finding ways toadd more generation capacity to meet future needs, both of which areexpensive. Moreover, burgeoning energy consumption continues tonegatively impact the environment and deplete natural resources.

Such concerns underlie recent industry and governmental efforts tostrive for a better balance between energy supply and consumption. Forexample, the Zero Net Energy (ZNE) concept, supported by the U.S.Department of Energy, promotes the ideal of a building with ZNEconsumption, in that the total energy used by the building annuallybalances with the total energy generated on-site. In California, the2013 Integrated Energy Policy Report (IEPR) builds on earlier ZNE goalsfor California by mandating that all new residential and all newcommercial construction be ZNE compliant, respectively, by 2020 and2030. The IEPR also goes a bit further to define a building as consumingzero net energy, where the net amount of energy produced by on-siterenewable energy resources roughly equals the value of the energyconsumed by the building annually.

Balancing energy use is challenging. The average consumer continuallyconsumes energy for many different purposes, all of which effect, eitherdirectly or implicitly, energy costs and the environment. At home,energy may be consumed for space heating and cooling, lighting, cooking,powering appliances and electrical devices, heating water, and doinglaundry. As well, energy may originate from different supply sources,including energy purchased from a power utility or, less frequently,generated on-site. In addition, where walking, bicycling or otherphysical modes of travel are impracticable, energy may also be used forpersonal transportation, whether via private conveyance or by publicmass transit.

The net effect of personal energy use adds up. Making any kind of changeis a two-fold problem that requires careful deliberation, which firstrequires knowing, in tangible terms, what energy is consumed for whatpurpose. Energy used for personal transportation can be readilydetermined based on regular travel patterns and the average costs offuel and vehicle maintenance. However, absent a detailed energy audit,the contributions of individual components in the home to overall energyconsumption are less certain, and establishing a baseline of personalhome energy consumption can be difficult due to the range of unknowns.For instance, the cost of electricity tends to be variable, based onseason, time of day, and amount consumed, yet calculating electricitycosts requires precisely knowing how much electricity is consumed bywhat components at what times.

Once energy consumption knowledge has been established, changingpersonal energy consumption requires determining what energy options oralternatives exist that work most efficaciously and, if applicable,which best move the consumer towards a ZNE consumption paradigm.Choosing between energy options and alternatives requires evaluating howhome and vehicle selections affect energy consumption, and knowing howenergy supply decisions affect costs and environmental impact. However,conventional ways to help consumers make sound energy option andalternative choices have been inadequate due to the option space thatmust be explored, and forecasting the expected balance between the costsversus benefits of different option scenarios has been unsatisfactory.

Therefore, a need remains for an approach to empowering consumers,particularly residential customers, with answers on personal energyconsumption and understanding what options and alternatives work bestfor their energy needs.

SUMMARY

The percentage of the total fuel purchased for space heating purposescan be fractionally inferred by evaluating annual fuel purchase data. Anaverage of monthly fuel purchases during non-heating season months isfirst calculated. The fuel purchases for each month is then compared tothe average monthly fuel purchase, where the lesser of the average andthat month's fuel purchase are added to a running total of annual spaceheating fuel purchases.

In addition, the overall thermal performance of a building UA^(Total)can be empirically estimated through a short-duration controlled test.Preferably, the controlled test is performed at night during the winter.A heating source, such as a furnace, is turned off after the indoortemperature has stabilized. After an extended period, such as 12 hours,the heating source is turned back on for a brief period, such as onehour, then turned back off. The indoor temperature is allowed tostabilize. The energy consumed within the building during the testperiod is assumed to equal internal heat gains. Overall thermalperformance is estimated by balancing the heat gained with the heat lostduring the test period.

Furthermore, potential energy investment scenarios can be evaluated.Energy performance specifications and prices for both existing andproposed energy-related equipment are selected, from which an initialcapital cost is determined. The equipment selections are combined withcurrent fuel consumption data, thermal characteristics of the building,and solar resource and other weather data to create an estimate of thefuel consumption of the proposed equipment. An electricity bill iscalculated for the proposed equipment, from which an annual cost isdetermined. The payback of the proposed energy investment is found bycomparing the initial and annual costs.

Finally, new energy investments specifically affecting buildingenvelope, heating source, or heating delivery can be evaluated. Datathat can include the percentage of a fuel bill for fuel used for heatingpurposes, an existing fuel bill, existing overall thermal propertiesUA^(Total) of the building, existing furnace efficiency, new furnaceefficiency, existing delivery system efficiency, new delivery systemefficiency, areas of building surfaces to be replaced or upgraded,existing U-values of thermal properties of building surfaces to bereplaced or upgraded, new U-values of thermal properties of buildingsurfaces to be replaced or upgraded, and number of air changes beforeand after energy investment are obtained. The impact of energyinvestments that affect heat transfer through the building envelope dueto conduction, heat losses due to infiltration, or both, are quantifiedby a comparative analysis of relative costs and effects on thebuilding's thermal characteristics, both before and after the proposedchanges.

One embodiment provides a system and method for empirical-test-basedestimation of overall thermal performance of a building with the aid ofa digital computer. A non-transitory computer readable storage mediumcomprising program code, a heating source including a heating elementand a heating delivery component comprised inside a building, athermometer comprised inside the building, and a thermometer locatedoutside of the building are provided. A computer processor interfaced tothe storage medium and remotely interface, the heating source, theinside thermometer, and the outside thermometer is provided, wherein thecomputer processor is configured to execute the program code. Operationof the heating source is stopped with the computer processor at thebeginning of an unheated period after recording with the computerprocessor into the storage medium a baseline indoor temperature from theindoor thermometer and a baseline outdoor temperature from the outdoorthermometer. Operation of the heating source is temporarily resumed withthe computer processor at the end of the unheated period after recordinginto the storage medium a starting indoor temperature from the indoorthermometer. Operation of the heating source is stopped with thecomputer processor after running the heating source for a heated periodand a final indoor temperature from the indoor thermometer after astabilizing period following the heated period is recorded with thecomputer processor into the storage medium. Energy consumed in thebuilding is measured with the computer processor from the beginning ofthe unheated period to the ending of the stabilizing period as equalingheat gained inside the building from internal sources of heat. Anexpected final indoor temperature at the end of the stabilizing periodis estimated with the computer processor based on the heating source nothaving been run for the heated period. The heat gained inside thebuilding over the heating period through operation of the heating sourceis determined with the computer processor using the fuel requirements ofthe heating source, the efficiency of the heating source, and theefficiency of the heating delivery component. Overall thermalperformance of the building is estimated with the computer processorusing the heat gained through using the heating source, the measuredenergy, the indoor temperatures, the baseline outdoor temperature, andthe estimated final indoor temperature.

Still other embodiments will become readily apparent to those skilled inthe art from the following detailed description, wherein are describedembodiments by way of illustrating the best mode contemplated. As willbe realized, other and different embodiments are possible and theembodiments' several details are capable of modifications in variousobvious respects, all without departing from their spirit and the scope.Accordingly, the drawings and detailed description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a Venn diagram showing, by way of example, a typicalconsumer's energy-related costs.

FIG. 2 is a flow diagram showing a function for fractionally inferringthe percentage of the total fuel purchased for space heating purposes,in accordance with one embodiment.

FIG. 3 is a graph depicting, by way of example, annual fuel purchases,including fuel purchased for space heating purposes.

FIG. 4 is a flow diagram showing method for empirically estimatingoverall thermal performance of a building through a short-durationcontrolled test, in accordance with one embodiment.

FIG. 5 is a graph depicting, by way of example, the controlled,short-duration test of FIG. 4.

FIG. 6 is a graph depicting, by way of example, the controlled,short-duration test of FIG. 4 for a different day.

FIG. 7 is a screen shot showing, by way of example, an analysis ofenergy investment choices.

FIG. 8 is a process flow diagram showing a computer-implemented methodfor evaluating potential energy investment scenarios from a user'sperspective, in accordance with one embodiment.

FIG. 9 is a detail of the graphical user interface of FIG. 7 showing, byway of example, an annotated graph of hourly electricity consumption.

FIG. 10 is a process flow diagram showing a routine for evaluatingpotential energy investment payback for use in the method of FIG. 8.

FIG. 11 is a graph depicting, by way of example, assumed hourlydistribution factors, as determined by the routine of FIG. 10.

FIG. 12 is a flow diagram showing a computer-implemented method forevaluating potential energy investment scenarios specially affecting abuilding's envelope, heating source, or heating delivery, in accordancewith a further embodiment.

FIG. 13 is a process flow diagram showing a routine for selecting energyinvestment scenario parameters for use in the method of FIG. 12.

FIG. 14 is a block diagram showing a computer-implemented system 140 forempirically estimating overall thermal performance of a building througha short-duration controlled test, in accordance with one embodiment.

DETAILED DESCRIPTION

Private individuals enjoy an immediacy to decision-making on matters ofenergy consumption and supply. As a result, individuals are ideallypositioned to effect the kinds of changes necessary to decrease theirpersonal energy consumption and to choose appropriate sources of energysupply, among other actions. However, merely having an ability ormotivation to better balance or reduce energy consumption, includingadopting a ZNE goal, are not enough, as the possible ways that personalenergy consumption can be decreased are countless, and navigatingthrough the option space can be time-consuming and frustrating.Individual consumers need, but often lack, the information necessary toguide the energy consumption and supply decisions that are required toaccomplish their goals.

The problem of providing consumers with the kinds of information neededto wisely make energy-related decisions can be approached by firstdeveloping a cost model, which depicts the energy consumption landscapeof the average consumer.

Brief Description of the Drawings

FIG. 1 is a Venn diagram showing, by way of example, a typicalconsumer's energy-related costs 10. The costs 10 include both fuel costsand operational costs, which provide the basis of the cost model. Forpurposes of illustration, the cost model assumes that the hypotheticalconsumer has a private residence, as opposed to an apartment orcondominium, and uses a personal vehicle as a primary mode oftransportation, rather than public mass transit or a physical mode oftravel. The cost model can be adapted mutatis mutandis to other modelingscenarios for apartment dwellers or urban city commuters, for instance,who may have other energy consumption and supply types of expenses.

The cost model builds on the choices made by consumers that affect theirenergy consumption. For example, residential consumers must choosebetween various energy options or alternatives concerning weatherstripping or caulking to seal a house; increased ceiling, floor, andwall insulation; high-efficiency windows; window treatments;programmable thermostats; cool roofs, that is, roofs that have a highsolar reflectance; radiant barriers; roof venting; electric and naturalgas furnaces for space heating; air source and geothermal heat pumps forspace heating and cooling; compressive and evaporative air conditioners;natural gas and electric, tank-based, and tank-less water heaters; airsource heat pump water heaters; fluorescent and LED lights; highefficiency appliances, including clothes washers, clothes dryers,refrigerators, dishwashers, and microwave ovens; electric (conductiveand inductive) and natural gas stoves; electric and natural gas ovens;and electronic equipment that consume electricity, such as Wi-Firouters, televisions, stereos, and so on. Consumers who rely onnon-physical modes of travel must choose between standard gasoline- ordiesel-fueled vehicles; hybrid gasoline- or diesel-fueled vehicles;natural gas vehicles; plug-in hybrid electric vehicles; and pureelectric vehicles. The situation is further complicated in thatconsumers have choices in energy supply, in addition to their choice intheir energy purchases. These choices include purchasing energy, thatis, electricity and natural gas, from their local utility; purchasinggasoline, diesel or other automobile fuel from a gasoline station;generating hot water using solar hot water heating; and generatingelectricity, either for home or transportation purposes, usingphotovoltaic power generation systems or, less commonly, small wind,small hydroelectric, or other distributed power generation technologies.

In the cost model, the energy-related costs 10 can be divided intocategories for home energy costs 11 and personal transportation costs12. In the home, energy may be consumed for space heating and cooling13, lighting 14, cooking 15, powering appliances and electrical devices16, heating water 17, and doing laundry 18, although fewer or more homeenergy costs may also be possible, such as where a consumer lacksin-home laundry facilities. Personal transportation costs may includethe actual cost of the vehicle 19, as well as fuel costs 20 andmaintenance expenses 21, although fewer or more transportation costs mayalso be possible, such as where a company car is provided to theconsumer free of charge.

For purposes of the cost model, fuel costs include electricity (E); fuelfor heating (F), which could be natural gas, propane, or fuel oil; andfuel for transportation (G), which could be gasoline, diesel, propane,LPG, or other automobile fuel. In addition, maintenance costs will beincluded in the cost model. A consumer's total energy-related costs(C^(Total)) equals the sum of the electricity cost (C^(E)), fuel forheating cost (C^(F)), gasoline (or other automobile fuel) cost (C^(G)),and maintenance cost (C^(M)), which can be expressed as:

C ^(Total) =C ^(E) +C ^(F) +C ^(G) +C ^(M)  (1)

In Equation (1), each cost component can be represented as the productof average price and annual quantity consumed, assuming that the priceis zero when the quantity consumed is zero. As a result, the totalenergy-related costs C^(Total) can be expressed as:

C ^(Total) =P ^(E) Q ^(E) +P ^(F) Q ^(F) +P ^(G) Q ^(G) +P ^(M) Q^(M)  (2)

Price and quantity in Equation (2) need to be consistent with eachother, but price and quantity do not need to be the same across all costcomponents. Fuel units depend upon the type of fuel. Electricity price(P^(E)) is expressed in dollars per kilowatt hour ($/kWh) andelectricity quantity (Q^(E)) is expressed in kilowatt hours (kWh). Fornatural gas, fuel for heating price (P^(F)) is expressed in dollars perthermal unit ($/therm) and fuel quantity (Q^(F)) is expressed in thermalunits (therms). Gasoline (or other automobile fuel) price (P^(G)) isexpressed in dollars per gallon ($/gallon) and gasoline quantity (Q^(G))is expressed in gallons. If only automobile maintenance costs areincluded and not the vehicle cost, maintenance price (P^(M)) can be indollars per mile driven ($/mile) and maintenance quantity (Q^(M)) can beexpressed in miles.

Pricing of fuel for heating (P^(F)) may be a function of the amount offuel consumed or could be a non-linear value, that is, a valuedetermined independent of amount used, or a combination of amount andseparate charges. In the cost model, for clarity, the fuel for heatingcost (C^(F)) assumes that the quantity of fuel actually used for spaceheating is separable from other loads in a home that consume the sametype of fuel, as further explained infra.

For fuels for heating sold by bulk quantity, such as propane or fueloil, fuel pricing is typically on a per-unit quantity basis. For otherfuels for heating, such as natural gas, a number of utilities havetiered natural pricing that depend upon the quantity consumed. Inparticular, electricity pricing can be complicated and may depend upon avariety of factors, including the amount of electricity purchased over aset time period, such as monthly, for instance, tiered electricityprices; the timing of the electricity purchases, for instance,time-of-use electricity prices; fixed system charges; and so forth. As aresult, accurately calculating average electricity pricing oftenrequires detailed time series electricity consumption data combined withelectricity rate structures. Conventional programs and online servicesare available to perform electricity pricing calculations. A slightlydifferent formulation of electricity pricing may be used where thequantity of electricity purchased nets out to zero consumption, but thetotal cost does not, such as can occur due to a flat service surcharge.

In the cost model, the quantity of electricity (Q^(E)), fuel for heating(Q^(F)), and gasoline (or other automobile fuel) (Q^(G)) purchased isassumed to equal the quantity consumed for meeting the consumer's energyconsumption requirements.

Gasoline (or other automobile fuel) fuel quantity (Q^(G)) can be fairlyestimated based on miles driven annually over observed or stated vehiclefuel efficiency, such as available from http://www.fueleconomy.gov.Electricity quantity (Q^(E)) can generally be obtained from powerutility bills.

The quantity of fuel for heating (Q^(F)) grossly represents the amountof fuel that needs to be purchased to provide the desired amount of heatin the consumer's home. The amount of fuel used for heating may actuallybe smaller than the total amount of fuel delivered to the home;depending upon the types of components installed in a home, the fuelused for heating may also be the same fuel used for other purposes,which may include fuel used, for example, for heating water, cooking, ordrying clothes. Notwithstanding, utilities that provide fuel to theircustomers for heating and other purposes, in particular, natural gas,via piped-in public utility service generally meter net fuel purchasesat the point of delivery. Individual loads are not metered. Thus, thetotal quantity of fuel (Q^(F)) consumed may need to be divided into theamount of fuel used strictly for space heating (Q^(F-Heating)) and theamount of fuel used for other non-space heating purposes(Q^(F-Non-Heating)). For instance, in many residential situations, muchof the non-space heating fuel will be used for water heating. Theload-corrected quantity of fuel (Q^(F)) can be expressed as:

Q ^(F) =Q ^(F-Heating) +Q ^(F-Non-Heating)  (3)

Modeling the quantity of fuel consumed for space heating (Q^(F))requires consideration of the type of space heating employed in a home.A separate quantity of fuel for space heating is only required if thetype of heating system used does not use electricity for active heatgeneration. Active heating sources, such as central heating systems,include a heating element that heats the air or water, for instance, afurnace or boiler, and a heating delivery or distribution component,such as ductwork through which the heated air is forced by an electricfan or pipes through which the heated water is circulated via anelectric pump. Thus, where the heating element requires, for instance,natural gas, propane, or fuel oil to generate heat, the quantity of fuelfor space heating consumed will be equal to the consumer's energyconsumption for space heating requirements. In contrast, where theheating element relies on electricity for active heat generation, suchas passive radiant heating or an electric-powered air source heat pump,the quantity of fuel for space heating will be zero, although the totalquantity of electricity (Q^(E)) consumed will be significantly higherdue to the electricity used for heat generation. The fuel for spaceheating quantity (Q^(F)) can be normalized to the quantity ofelectricity (Q^(E)) for purposes of comparison. Estimating the amount offuel consumed for space heating requirements will now be discussed.

The overall rate of heat transfer of a building equals the rate of theheat transfer or conduction through each unique building surface plusthe rate of heat transfer through infiltration, that is, air leakageinto a building. Conduction rate and infiltration rate are based on thethermal characteristics of the material in each surface of the buildingand upon the indoor and outdoor temperatures and airtightness of thebuilding.

Heat transfer can be individually calculated for each building surface,then summed to yield overall heat transfer. Alternatively, a building'soverall thermal performance (UA^(Total)) can first be calculated,expressed in units of Btu per ° F.-hour. Overall thermal performance canthen be combined with the difference between the indoor and outdoortemperature. When the latter approach is used, the heat loss over aone-hour period Q^(Heat Loss) equals UA^(Total) times the differencebetween the average indoor and outdoor temperature times one hour, whichcan be expressed as:

Q ^(Heat Loss)=(UA ^(Total))(T _(Indoor) −T _(Outdoor))(1 hour)  (4)

Equation (4) can be rearranged to yield UA^(Total):

$\begin{matrix}{{UA}^{Total} = \frac{Q^{{Heat}\mspace{14mu} {Loss}}}{\left( {T_{Indoor} - T_{Outdoor}} \right)\left( {1\mspace{14mu} {hour}} \right)}} & (5)\end{matrix}$

Total heat loss Q^(Heat Loss) can be analytically estimated based onfurnace sizing for the building, such as described in H. Rutkowski,Manual J Residential Load Calculation, (8^(th) ed. 2011) (“Manual J”),and also as provided via the Air

Conditioning Contractors of America's Web-fillable Form RPER 1.01,available at http://ww.acca.org. Per the Manual J approach, winter andsummer design conditions are specified, including indoor and outdoortemperatures. In addition, surface measurements and materials, estimatedinfiltration, heating and cooling equipment capacities, and ductdistribution system design are specified.

These values are used in the Manual J approach to estimate total heatloss per hour, from which a recommended heating output capacity isdetermined. For example, a heating system having a 64,000 Btu/hourheating output capacity would be appropriate in a building with anestimated total heat loss of 59,326 Btu/hour. Assuming an outdoortemperature of −6° F. and an indoor temperature of 70° F., Equation (5)can be used to estimate UA^(Total) based on the estimated total heatloss of 59,326 Btu/hour, such that:

$\begin{matrix}{{UA}^{Total} = {\frac{59,326\mspace{14mu} {Btu}}{\left\lbrack {70{^\circ}\mspace{14mu} {F.{- \left( {{- 6}{^\circ}\mspace{14mu} {F.}} \right)}}} \right\rbrack \left( {1\mspace{14mu} {hour}} \right)} = \frac{781\mspace{14mu} {Btu}}{{{^\circ}F}\text{-}{hour}}}} & (6)\end{matrix}$

The result is that this building's overall thermal performance is 781Btu/hr-° F. Other ways of estimating total heat loss Q^(Heat Loss) arepossible.

Equation (4) provides an estimate of the heat loss over a one-hourperiod Q^(Heat Loss) for a building. Equation (4) can also be used toderive the amount of heat that needs to be delivered to a buildingQ^(Heat Delivered) by multiplying the building's overall thermalperformance UA^(Total), times 24 hours per day, times the number ofHeating Degree Days, such as described in J. Randolf et al., Energy forSustainability: Technology, Planning, Policy, p. 248 (2008), which canbe expressed as:

Q ^(Heat Delivered)=(UA ^(Total))(24)(HDD _(Location)^(Set Point Temp))  (7)

The number of Heating Degree Days, expressed as HDD_(Location)^(Set Point Temp) in ° F.-day per year, is determined by the desiredindoor temperature and geographic location and can be provided by lookuptables.

In turn, the annual amount of heat delivered by a furnace to a buildingfor end-use Q^(Heat Delivered-Furnace), expressed in Btu per hour,equals the product of furnace fuel requirements R^(Furnace), alsoexpressed in Btu per hour, percentage of furnace efficiency η^(Furnace),percentage of delivery system efficiency η^(Delivery), and hours ofoperation Running-Time, such that:

Q ^(Heat Delivered-Furnace)=(R^(Furnace))(η^(Furnace)η^(Delivery))(Running-Time)  (8)

The annual amount of heat delivered Q^(Heat Delivered-Furnace) can bediscounted by the amount of energy passively obtained on-site. Forinstance, if the solar savings fraction (SSF) represents the fraction ofenergy by a building due to solar gains, the heat that needs to bedelivered by the furnace can be expressed by:

Q ^(Heat Delivered-Furnace) =Q ^(Heat Delivered)(1−SFF)  (9)

For the time being, ignore any gains in indoor temperature due tointernal sources of heat.

The amount of fuel used strictly for space heating Q^(F-Heating) can befound by substituting Equation (7) into Equation (9), setting the resultequal to Equation (8), and solving for Q^(F-Heating). The amount of fuelthat needs to be purchased for space heating uses Q^(F-Heating) equalsthe product of furnace fuel requirements R^(Furnace) and hours ofoperation hours Running-Time. Thus, solving for Q^(F-Heating).

$\begin{matrix}{Q^{F\text{-}{Heating}} = \frac{\left( {UA}^{Total} \right)(24)\left( {HDD}_{Location}^{{Set}\mspace{14mu} {Point}\mspace{14mu} {Temp}} \right)\left( {1 - {SSF}} \right)}{\eta^{Furnace}\eta^{Delivery}}} & (10)\end{matrix}$

Calculating the solar savings fraction SSF typically requires extensivecomputer modeling. However, for an existing building, the SSF can bedetermined by setting Equation (10) equal to the amount of fuel requiredfor space heating and solving for the solar savings fraction.

In general, utilities that provide fuel to their customers via piped-inpublic utility services meter fuel purchases at the point of deliveryand not by individual component load. In situations where the fuel isused for purposes other than solely space heating, the total fuelpurchased for space heating Q^(F-Heating) may only represent a fractionof the total fuel purchased Q^(F). Q^(F-Heating) can be expressed as:

Q ^(F-Heating)=(H)(Q ^(F))  (11)

where H fractionally represents the percentage of the total fuelpurchased for space heating purposes.

The fraction H can be empirically inferred from fuel purchase data. Fuelpurchased in the months occurring outside of the heating season areassumed to represent the fuel purchased for non-space heating needs andcan be considered to represent a constant baseline fuel expense. FIG. 2is a flow diagram showing a function 30 for fractionally inferring thepercentage of the total fuel purchased for space heating purposes, inaccordance with one embodiment. The function 30 can be implemented insoftware and execution of the software can be performed on a computersystem, such as further described infra with reference to FIG. 14, as aseries of process or method modules or steps.

Initially, fuel purchase data is obtained (step 31), such as can beprovided by the fuel utility. Preferably, the data reflects fuelpurchases made on at least a monthly basis from the utility. An averageof the fuel purchased monthly during non-heating season months iscalculated (step 32). In some regions, the heating season will onlyinclude traditional winter months, beginning around mid-December andending around mid-March; however, in most other regions, space heatingmay be required increasingly in the months preceding winter anddecreasingly in the months following winter, which will result in anextended heating season.

Each month (or time increment represented by each fuel purchase) is theniteratively processed (steps 33-40), as follows. For each month (step33), the fuel purchase for that month is chosen (step 34) and added to arunning total of annual fuel purchases (step 35). If the monthly fuelpurchase is greater than the average of the fuel purchased monthlyduring non-heating season months (step 36), the average of the fuelpurchased monthly is subtracted from that monthly fuel purchase (step37) and the remainder represents the fuel purchased for space heating inthat month. Otherwise, the monthly fuel purchase is subtracted fromitself (step 38), effectively indicating that the fuel purchased forspace heating in that month is zero. The difference of the subtraction,that is, the fuel purchased for space heating in that month, is added toa running total of annual space heating fuel purchases (step 39), andthe process repeats for each subsequent month (step 40). Finally, theratio of the running total of annual space heating fuel purchases to therunning total of annual fuel purchases is returned (step 41) as thefraction H.

The relationship between total annual fuel purchases and total annualspace heating fuel purchases can be visualized. FIG. 3 is a graph 50depicting, by way of example, annual fuel purchases, including fuelpurchased for space heating purposes. The x-axis 51 represents months.The y-axis 52 represents natural gas consumption, expressed in thermsper day. May through September are considered non-winter (non-heatingseason) months. The natural gas (fuel) purchases 53 for each month aredepicted as circles. Total annual fuel purchases 54 can be interpolatedby connecting each monthly natural gas purchase 53. The fraction H forthe percentage of the total fuel purchased for space heating purposeseach month is determined, from which a baseline annual fuel expense 55can be drawn. The region between the baseline annual fuel expense 55 andthe interpolated total annual fuel purchases 54 represents the totalannual space heating (fuel) purchases 56.

The relationship between the total annual fuel purchases, baseline fuelexpenses, and total space heating purchases can be formalized. First,the average monthly fuel purchased for non-winter monthsQ^(F-Non-Winter) over a set number of months is calculated, as follows:

$\begin{matrix}{\overset{\_}{Q^{F\text{-}{Non}\text{-}{Winter}}} = \frac{\sum\limits_{i = {{Non}\text{-}{Winter}\mspace{14mu} {Start}\mspace{14mu} {Month}}}^{{Non}\text{-}{Winter}\mspace{14mu} {End}\mspace{14mu} {Month}}{{Fuel}\mspace{14mu} {Purchased}_{i}}}{{Number}\mspace{14mu} {of}\mspace{14mu} {Months}}} & (12)\end{matrix}$

where i represents the range of non-winter months within the set numberof months; and Fuel Purchased_(i) represents the fuel purchased in thenon-winter month i.

Next, the fuel consumed each month for heating, which is the differencebetween the monthly fuel purchase and the minimum of either the monthlyfuel purchase or the average monthly fuel purchased for non-wintermonths, is added to a summation to yield the total annual fuel consumedfor heating Q^(F-Heating), as follows:

$\begin{matrix}{Q^{F\text{-}{Heating}} = {\sum\limits_{i = 1}^{12}\left( {{{Fuel}\mspace{14mu} {Purchased}_{i}} - {\min\left( {{{Fuel}\mspace{14mu} {Purchased}_{i}},\overset{\_}{Q^{F\text{-}{Non}\text{-}{Winter}}}} \right)}} \right)}} & (13)\end{matrix}$

Assuming that the total annual fuel purchases Q^(F) are non-zero, theratio of the total annual fuel consumed for heating Q^(F-Heating) andthe total fuel purchases Q^(F) is taken to yield the fraction H, asfollows:

$\begin{matrix}{H = \frac{Q^{F\text{-}{Heating}}}{Q^{F}}} & (14)\end{matrix}$

Finally, the percent of heat supplied by the solar savings fraction canbe determined by setting Equation (10) equal to Equation (11) andsolving for SSF, in accordance with:

$\begin{matrix}{{SSF} = {1 - \frac{(H)\left( Q^{F} \right)\left( \eta^{Furnace} \right)\left( \eta^{Delivery} \right)}{\left( {UA}^{Total} \right)(24)\left( {HDD}_{Location}^{{Set}\mspace{14mu} {Point}\mspace{14mu} {Temp}} \right)}}} & (15)\end{matrix}$

A building's overall thermal performance UA^(Total) is key to estimatingthe amount of fuel consumed for space heating requirements. Equation(5), discussed supra, presents one approach to estimating UA^(Total),provided that the total heat loss Q^(Heat Loss) can be estimated. Ananalytical approach to determining UA^(Total) requires a detailed energyaudit, from which UA^(Total) is then calculated using a set ofindustry-standard engineering equations. With both approaches, thebuilding's actual thermal performance is not directly measured. A thirdapproach through UA^(Total) can be empirically quantified will now bepresented.

The total heat transfer of a building at any instant in time (q^(Total))equals the sum of the heat transferred through the building envelope byconduction (q^(Envelope)) plus the heat transferred through infiltration(q^(Infiltration)), which can be expressed as:

q ^(Total) =q ^(Envelope) +q ^(Infiltration)  (16)

An energy audit does not directly measure the heat transferred throughthe building envelope by conduction q^(Envelope). Rather, q^(Envelope)is calculated using a series of steps. First, the surface areas of allnon-homogeneous exterior-facing surfaces are either physically measuredor verified, such as by consulting plans for the building.Non-homogeneous surfaces are those areas that have different insulatingmaterials or thicknesses. The surface areas of all floors, walls,ceilings, and windows are included.

Second, the insulating properties of the materials used, quantified as“R-values,” or the capacity of an insulating material to resist heatflow for all surfaces area determined. R-values are generally determinedby visual inspection, if the insulation is exposed, such as insulationbatts used in an attic. When the insulation cannot be visuallyinspected, as with wall insulation, R-values are estimated based onsurface thickness and the age of the building.

These first two steps are difficult, time-consuming, and carry the riskof mistakes. Accurately measuring all of the exterior-facing surfacescan be tedious, and the manual nature of the visual inspection admits oferror. For instance, some wall surfaces may appear to be onlyinterior-facing, yet parts of a wall may actually be both interior- andexterior-facing, as can happen in a split-level home along the walldividing the “split” sections of the house (also referred to as a kneewall). When viewed from inside, the wall along the split, on both sides,appears to be an interior-facing wall, yet the upper section of thatwall is often partially exposed to the exterior along the outer wallsurface extending beyond the ceiling height of the lower section of thesplit. In addition, issues, such as improperly installed insulation andinsulation falling away from a wall, can be missed by a visualinspection.

Third, the R-values are inverted to yield U-values, which are thenmultiplied by their corresponding surface areas. The results are summedacross all N surfaces of the building. Total heat transfer through thebuilding envelope by conduction q^(Envelope) equals the product of thissummation times the difference between the indoor and outdoortemperatures, expressed as:

$\begin{matrix}{q^{Envelope} = {\left( {\sum\limits_{i = 1}^{N}{U^{i}A^{i}}} \right)\left( {T^{Indoor} - T^{Outdoor}} \right)}} & (17)\end{matrix}$

where U^(i) represents the U-value of surface i; A^(i) represents thesurface area of surface i; and T^(Indoor) and T^(Outdoor) arerespectively the indoor and outdoor temperatures relative to thebuilding.

Heat transfer also occurs due to infiltration. “A major load for yourfurnace is heating up cold air leaking into your house, while warmindoor air leaks out. These infiltration losses are driven in part bythe difference in the indoor-to-outdoor temperature (stack-driveninfiltration) and in part by the pressure differences caused by the windblowing against the side of the house (wind-driven insolation).” J.Randolf et al. at p. 238, cited supra. Formally, the rate of heattransfer due to infiltration q^(Infiltration) can be expressed as:

q ^(Infiltration) =ρcnV(T ^(Indoor) −T ^(Outdoor))  (18)

where ρ represents the density of air, expressed in pounds per cubicfoot; c represents the specific heat of air, expressed in Btu per pound° F.; n is the number of air changes per hour, expressed in number perhour; and V represents the volume of air per air change, expressed incubic feet per air change.

In Equation (18), ρ and c are constants and are the same for allbuildings; ρ equals 0.075 lbs/ft³ and c equals 0.24 Btu/lb-° F. n and Vare building-specific values. V can be measured directly or can beapproximated by multiplying building square footage times the averageroom height. Measuring n, the number of air changes per hour, requiressignificant effort and can be directly measured using a blower doortest.

Total heat transfer q^(Total) can now be determined. To review,q^(Total) equals the sum of the heat transfer through the buildingenvelope by conduction q^(Envelope) plus the heat transfer throughq^(Infiltration). Substitute Equation (17) and Equation (18) intoEquation (16) to express the rate of heat loss q^(Total) for bothcomponents:

q ^(Total) =UA ^(Total)(T ^(Indoor) −T ^(Outdoor))  (19)

where:

$\begin{matrix}{{UA}^{Total} = {\left( {\sum\limits_{i = 1}^{N}{U^{i}A^{i}}} \right) + {\rho \mspace{14mu} c\mspace{14mu} n\mspace{14mu} V}}} & (20)\end{matrix}$

Equation (19) presents the rate of heat transfer q^(Total) at a giveninstant in time. Instantaneous heat transfer can be converted to totalheat transfer over time Q_(Δt) ^(Total) by adding a time subscript tothe temperature variables and integrating over time. UA^(Total) isconstant over time. Integrating Equation (19), with UA^(Total) factoredout, results in:

Q _(Δt) ^(Total) =UA ^(Total)

_(t) ₀ ^(t) ⁰ ^(+Δt)(T _(t) ^(Indoor) −T _(t) ^(Outdoor))dt  (21)

Equation (21) can be used in several ways. One common application of theequation is to calculate annual fuel requirements for space heating.Building occupants typically desire to maintain a fixed indoortemperature during the summer and a different fixed indoor temperatureduring the winter. By the same token, building operators typically wantto determine the costs of maintaining these desired indoor temperatures.

For example, take the case of maintaining a fixed indoor temperatureduring the winter. Let the temperature be represented byT^(Indoor-Set Point Temp) and let Δt equal one year. Equation (21) canbe modified to calculate the annual heat loss Q_(Annual) ^(Heat Loss) byadding a maximum term, such that:

Q _(Annual) ^(Heat Loss) =UA ^(Total)

_(t) ₀ ^(t) ⁰ ^(+Δt)max (T _(t) ^(Indoor-Set point Temp) −T _(t)^(Outdoor),0)dt  (22)

Solving Equation (22) yields:

Q _(Annual) ^(Heat Loss) =UA ^(Total)(24*HDD^(Indoor-Set Point Temp))  (23)

where HDD represents the number of degree days when the outdoortemperature exceeds the desired indoor temperature. A typical indoortemperature used to calculate HDD is 65° F.

Equation (23) is a widely-used equation to calculate annual heat loss.UA^(Total) is the core, building-specific parameter required to performthe calculation. UA^(Total) represents the building's overall thermalperformance, including heat loss through both the building envelopethrough conduction and heat loss through infiltration. Conventionalpractice requires an energy audit to determine UA^(Total), whichrequires recording physical dimension, visually inspecting or inferringR-values, and performing a blower door test. A formal energy audit canrequire many hours and can be quite expensive to perform. However,UA^(Total) can be empirically derived.

In slightly modified form, Equation (21) can be used to calculateHeating (or Cooling) Degree Days for estimating fuel costs for aone-year period by assuming that the indoor temperature is constant. Theequation can also be used to calculate short-term heat loss, as part ofan input to an empirical approach to deriving a building's overallthermal performance UA^(Total). FIG. 4 is a flow diagram showing methodfor empirically estimating overall thermal performance of a building 60through a short-duration controlled test, in accordance with oneembodiment. The method 60 requires the use of a controllable heating (orcooling) source, and the measurement and analysis aspects of the method60 can be implemented in software. Execution of the software can beperformed with the assistance a computer system, such as furtherdescribed infra with reference to FIG. 14, as a series of process ormethod modules or steps.

Briefly, the empirical approach is to perform a controlled test over ashort duration, for instance, 12 hours. During the controlled test, heatloss from a building occurs and a controllable heat source, such as afurnace, is subsequently used to compensate for the heat loss.Preferably, the controlled test is performed during the winter months.The same controlled test approach can be used during the summer months,where heat gain occurs and a controllable cooling source, such as an airconditioner, is subsequently used to compensate for the heat gain.

As a preliminary step, an appropriate testing period is chosen, duringwhich heat gain is controllable, such as during the night, when solargain will not be experienced. FIG. 5 is a graph depicting, by way ofexample, the controlled, short-duration test of FIG. 4. The x-axis 81represents time of day. The y-axis 82 represents temperature in ° F. Thetesting period is divided into an unheated period that occurs from timet₀ to time t₁, a heated period that occurs from time t₁ to time t₂, anda stabilizing period that occurs from time t₂ to time t₃. At a minimum,indoor temperature 83 is measured at times t₀, t₁, and t₃, althoughadditional indoor temperature measurements will increase the accuracy ofthe controlled test. Outdoor temperature 84 may optionally be measuredat times t₀ and t₃ and additional outdoor temperature measurements willalso increase the controlled test's accuracy. Additionally, an expectedfinal indoor temperature 85 is estimated based on a projection of whatthe indoor temperature would have been at time t₃, had the heatingsource not been turned back on at time t₁.

The starting time t_(o) of the unheated period should start when theindoor temperature has stabilized due to the effects of thermal mass.The unheated period is of a duration sufficient to allow for measurableheat loss, such as a period of around 12 hours, although other periodsof time are possible. The heating source is run for a short durationduring the heated period, such as for an hour or so, preferably early inthe morning before the sun rises. The stabilizing period provides a timelag for a short duration, such as an hour or so, to allow the indoortemperature to stabilize due to the effects of thermal mass. Otherfactors can be included in the controlled test, such as heat gain fromoccupants or other heat sources inside the building.

Referring back to FIG. 4, a baseline indoor temperature T₀ is recordedat the outset of an unheated period at time t₀ (step 61), at which timeoperation of the heating source is also stopped (step 62). The methodpauses during the unheated period from time t₀ to time t₁ (step 63). Astarting indoor temperature T₁ is recorded at the outset of a heatedperiod at time t₁ (step 64), at which time operation of the heatingsource is also temporarily resumed (step 65). The method pauses duringthe heated period from time t₁ to time t₂ (step 66). Operation of theheating source is again stopped at the end of the heated period at timet₂ (step 67). The method pauses during a stabilizing period from time t₂to time t₃ (step 68). A final indoor temperature T₃ is recorded at theend of a stabilizing period at time t₃ (step 69).

Next, the amount of energy consumed over testing period from time t₀ totime t₃ is measured (step 70). The energy is assumed to equal the totalamount of heat gained inside the building from internal sources of heat(Q^(Internal)); inclusion of independent sources of heat gain, such asfrom occupants, will increase accuracy. Finally, the overall thermalperformance of the building UA^(Total) and distribution efficiency areestimated (step 71), as follows.

First, the heat loss over the unheated period from time t₀ to time t₁ iscalculated, that is, by setting Δt to around 12 hours. Solving Equation(21) yields:

Q _(Δt) ^(Total) =UA ^(Total)( T _(Δt) ^(Indoor) − T _(Δt) ^(Outdoor))Δt  (24)

where T_(Δt) ^(Indoor) is the average indoor temperature and T_(Δt)^(Outdoor) is the average outdoor temperature.

Next, the heat gain by operating the heating source over the heatedperiod from time t₁ to time t₂ is calculated using Equation (8). Theamount of energy required to return the building to the baseline indoortemperature T₀ can be approximated by dividing the delivered heat by thepercent of heat loss that was restored using the controlled heat source.The amount of heat restored is assumed to be proportional to threetemperatures, the baseline indoor temperature T₀, the final indoortemperature T₃, and an expected final indoor temperature T₃ ^(No Heat),which is an estimated temperature based on a projection of what theindoor temperature would have been at time t₃, had the heating sourcenot been turned back on at time t₁. Assuming that T₀≠T₃ ^(No Heat), thepercentage of energy lost provided by the heat source equals:

$\begin{matrix}{{{Percent}\mspace{14mu} {Restored}} = \frac{T_{3} - T_{3}^{{No}\mspace{14mu} {Heat}}}{T_{0} - T_{3}^{{No}\mspace{14mu} {Heat}}}} & (25)\end{matrix}$

The hours of operation of the heating source equal t₂ minus t₁. Thus,the heat gain required to replace the lost heat equals Equation (8)divided by Equation (25), expressed as:

$\begin{matrix}{Q^{{Heat}\mspace{14mu} {Delivered}\text{-}{Furnace}} = {\left( R^{Furnace} \right)\left( {\eta^{Furnace}\eta^{Delivery}} \right)\left( {t_{2} - t_{1}} \right)\left( \frac{T_{0} - T_{3}^{{No}\mspace{14mu} {Heat}}}{T_{3} - T_{3}^{{No}\mspace{14mu} {Heat}}} \right)}} & (26)\end{matrix}$

In addition, heat was gained inside the building from internal sourcesof heat. Set Equation (33) plus heat delivered through internal gainsQ^(Internal) equal to Equation (24) and solve for overall thermalperformance UA^(Total):

$\begin{matrix}{{UA}^{Total} = \frac{\begin{matrix}{\left\lfloor \frac{\left( R^{Furnace} \right)\left( \eta^{Furnace} \right)\left( \eta^{Delivery} \right)\left( {t_{2} - t_{1}} \right)\left( {T_{0} - T_{3}^{{No}\mspace{14mu} {Heater}}} \right)}{\left( {T_{3} - T_{3}^{{No}\mspace{14mu} {Heater}}} \right)} \right\rfloor +} \\Q^{Internal}\end{matrix}}{\left( {T_{\Delta \; t}^{Indoor} - T_{\Delta \; t}^{Ambient}} \right)\left( {t_{3} - t_{0}} \right)}} & (27)\end{matrix}$

The controlled test approach has been empirically validated. The testingprocedure was conducted at approximately the same time of day on twoseparate days with different weather conditions for a house in Napa,Calif. The first test was started on Jan. 12, 2014 and the second testwas started on Jan. 13, 2014. There was a difference of about 15° F. inoutdoor temperature at the start of the testing on the two days. Inaddition, the heating source was only operated for the amount of timenecessary to return the house to the baseline temperature for the firsttest, while the heating source was not operated for a sufficiently longtime to return the house to the baseline temperature for the secondtest. The recorded indoor and outdoor temperatures for the testconducted on Jan. 12, 2014 is shown in FIG. 5. Similarly, FIG. 6 is agraph depicting, by way of example, the controlled, short-duration testof FIG. 4 for Jan. 13, 2014. As before, the x-axis represents time ofday and they-axis represents temperature in ° F. Assuming an 80%delivery efficiency η^(Delivery) results indicate that the house'soverall thermal performance UA^(Total) was 525 for the first test and470 for the second test. These results are within approximately 10percent of each other. In addition, an independent Certified Home EnergyRating System (HERS) rater was hired to perform an independent energyaudit of the house. The results of the HERS audit compared favorably tothe results of the empirical approach described supra with reference toFIG. 4.

The methods described herein can be used to equip consumers with thekinds of information necessary to make intelligent energy decisions. Anexample of how to apply the results to a particular situation will nowbe presented.

Example: A residential homeowner has an old heating, ventilation, andair conditioning (HVAC) system that is on the verge of failure. Theconsumer is evaluating two options:

Option 1: Replace the existing HVAC system with a system that has thesame efficiency and make no other building envelope investments in thehouse, at the cost of $9,000.

Option 2: Take advantage of a whole house rebate program that theconsumer's utility is offering and simultaneously upgrade multiplesystems in the house. The upgrades include increasing ceilinginsulation, replacing ductwork, converting the natural gas-powered spaceheating furnace and electric air conditioner to electric-powered airsource heat pumps, and providing enough annual energy to power the heatpump using a photovoltaic system.

In this example, the following assumptions apply:

-   -   The consumer's annual natural gas bill is $600, 60 percent of        which is for space heating. The natural gas price is $1 per        therm.    -   The existing furnace has an efficiency of 80 percent and the        existing ductwork has an efficiency of 78 percent.    -   Adding four inches of insulation to the 1,100 ft² ceiling, to        increase the R-Value from 13 to 26, will cost $300.    -   Photovoltaic power production costs $4,000 per kW_(DC), produces        1,400 kWh/kW_(DC)-yr, and qualifies for a 30-percent federal tax        credit.    -   The heat pump proposed in Option 2 has a Heating Season        Performance Factor (HSPF) of 9 Btu/Wh and a Seasonal Energy        Efficiency Ratio (SEER) identical to the existing air        conditioner. The heat pump will cost $10,000.    -   The ductwork proposed in Option 2 will be 97 percent efficient        and will cost $3,000.    -   The consumer will receive a $4,000 rebate from the utility for        the whole house upgrade under Option 2.

Analysis of the options requires determining the overall thermalcharacteristics of the existing building, evaluating the effects ofswitching fuel sources, comparing furnace efficiency, and determiningfuel requirements. For purposes of illustration, the calculation in theexample will only include the heating characteristics.

In this example, the consumer performed the empirical approach describedsupra with reference to FIG. 4 to empirically estimate overall thermalperformance of a building and determined that the UA^(Total) for hishouse was 450.

Option 2 presents multiple changes that need to be considered. First,Option 2 would require switching fuels from natural gas to electricity.Assume conversion factors of 99,976 Btu per therm and 3,412 Btu per kWh.Converting current energy usage, as expressed in therms, to anequivalent number of kWh yields:

$\begin{matrix}{Q^{F} = {{\left( {600\mspace{14mu} {thems}} \right)\left( \frac{99,976\mspace{14mu} {Btu}}{therm} \right)\left( \frac{1\mspace{14mu} {kWh}}{3,412\mspace{14mu} {Btu}} \right)} = {17,581\mspace{14mu} {kWh}}}} & (28)\end{matrix}$

Second, the heat pump is 264 percent efficient at converting electricityto heat. The equivalent furnace efficiency {circumflex over(η)}^(Furnace) of the heat pump is:

$\begin{matrix}{{\hat{\eta}}^{Furnace} = {{\left( \frac{9\mspace{14mu} {Btu}}{Wh} \right)\left( \frac{1,000\mspace{14mu} {Wh}}{kWh} \right)\left( \frac{1\mspace{14mu} {kWh}}{3,412\mspace{14mu} {Btu}} \right)} = {264\%}}} & (29)\end{matrix}$

Third, the annual amount of electricity required to power the heat pumpcan be determined with Equation (42), as further described infra, withthe superscript changed from ‘F’ (for natural gas fuel) to ‘E’ (forelectricity):

$\quad\begin{matrix}\begin{matrix}{{\hat{Q}}^{E\text{-}{Heating}} = {(0.6){\left( {17,581} \right)\left\lbrack {1 - \frac{\left( {\frac{1}{13} - \frac{1}{26}} \right)\left( {1,100} \right)}{450}} \right\rbrack}\left( \frac{0.80}{2.64} \right)\left( \frac{0.78}{0.97} \right)}} \\{= {2,351\mspace{14mu} {kWh}}}\end{matrix} & (30)\end{matrix}$

Fourth, in addition to switching from natural gas to electricity, theconsumer will be switching the source of the fuel from utility-suppliedelectricity to on-site photovoltaic power generation. The number ofkW_(DC) of photovoltaic power required to provide 2,329 kWh to power theheat pump can be found as:

$\begin{matrix}{{{PV}\mspace{14mu} {Capacity}\mspace{14mu} {Required}} = {\frac{2,351\mspace{14mu} {kWh}\text{/}{yr}}{1,400\mspace{14mu} {kWh}\text{/}{yr}} = {1.68\mspace{14mu} {kW}_{DC}}}} & (31)\end{matrix}$

Expected photovoltaic production can be forecast, such as described incommonly-assigned U.S. Pat. Nos. 8,165,811; 8,165,812; 8,165,813, allissued to Hoff on Apr. 24, 2012; U.S. Pat. Nos. 8,326,535 and 8,326,536,issued to

Hoff on Dec. 4, 2012; U.S. Pat. No. 8,335,649, issued to Hoff on Dec.18, 2012; U.S. Pat. No. 8,437,959, issued to Hoff on May 7, 2013; U.S.Pat. No. 8,577,612, issued to Hoff on Nov. 5, 2013; and U.S. patentapplication Ser. No. 14/058,121, filed Oct. 18, 2013, pending, thedisclosures of which are incorporated by reference.

Finally, as shown in Table 1, Option 2 will cost $14,025. Option 1 isthe minimum unavoidable cost of the two options and will cost $9,000.Thus, the net cost of Option 2 is $5,025. In addition, Option 2 willsave $360 per year in natural gas bills because 60-percent of the $600natural gas bill is for space, which represents a cost avoided. As aresult, Option 2 has a 14-year payback.

TABLE 1 Combined Item Cost Incentive Cost Increasing Ceiling Insulation  $300 Replace Ductwork  $3,000 Electric-Powered Air Source Heat $10,000Pump (Added Cost) Photovoltaic Power Generation (1.68  $6,720 kWpc @$4,000 per kWpc) Tax Credit for Photovoltaic Power ($1,995) GenerationUtility-Offered Whole House Rebate ($4,000) Total $20,020 ($5,995)$14,025

A building's overall thermal performance can be used to quantify annualenergy consumption requirements by fuel type. The calculations describedsupra assumed that energy prices did not vary with time of day, year, oramount of energy purchased. While this assumption is approximatelycorrect with natural gas and gasoline consumption, electricity prices dovary, with electric rate structures often taking into consideration timeof day, year, amount of energy purchased, and other factors.

Overall thermal performance, annual fuel consumption, and otherenergy-related estimates can be combined with various data sets tocalculate detailed and accurate fuel consumption forecasts, includingforecasts of electric bills. The fuel consumption forecasts can be used,for instance, in personal energy planning of total energy-related costsC^(Total), as well as overall progress towards ZNE consumption.

FIG. 7 is a screen shot showing, by way of example, the graphical userinterface (GUI) 90 of an energy investment choices analysis tool. Totalenergy-related costs C^(Total) include electricity cost (C^(E)), fuelfor heating cost (C^(F)), gasoline (or other automobile fuel) cost(C^(G)), and maintenance cost (C^(M)), as described supra with referenceto Equation (1), or for other energy planning purposes. Through theupper section 91 of the GUI 90, a user can select current and plannedenergy-related equipment and parameters. As applicable, the equipmentand parameters are evaluated in light of current energy data, includingconsumption data, building thermal characteristics, and historical solarresource and weather data, from which proposed energy data can begenerated as investment analysis results in the lower section 92 of theGUI 90.

The forecasts can be used to accurately model one or more energy-relatedinvestment choices, in terms of both actual and hypothesized energyconsumption and, in some cases, on-site energy production. The energyinvestment choices analysis tool of

FIG. 7 can be implemented through software. FIG. 8 is a process flowdiagram showing a computer-implemented method 100 for evaluatingpotential energy investment scenarios from a user's perspective, inaccordance with one embodiment. Execution of the software can beperformed on a computer system, such as further described infra withreference to FIG. 14, as a series of process or method modules or steps.The user interactively inputs energy-related investment selections andcan view analytical outputs through a graphical user interface.

As an initial step, using the GUI 90, a user makes selections 101 ofenergy-related equipment investments and parameters in the form ofenergy-consuming or (on-site) energy-producing equipment that arecurrently owned or that are under consideration for acquisition. Theanalysis tool helps the user to explore the various aspects of the totalenergy-related costs C^(Total) in terms of price and quantity, asdescribed supra with reference to Equation (2). If the user isinterested in just determining incurred capital cost or forecasting anelectric bill, the user need only enter information about existingequipment. If an energy equipment investment is being considered, theuser will need to select both the equipment currently in use and theequipment proposed to replace or upgrade the current equipment. Notethat the term “equipment” as used in the context of the analysis toolnon-exclusively includes multi-component systems, machinery, fixtures,appliances, and building structure, materials and components, any ofwhich could form the basis of an energy-related investment.Additionally, the term “parameters” refers to aspects of an investmentrelated more to operational use, than to the nature of the equipmentproper. For instance, energy consumption of a fixture, such as lighting,may be reduced by parametrically decreasing the hours of operation, inaddition to (or in lieu of) choosing a more energy-efficient form oflighting fixture. A pair of databases respectively store listings ofequipment 104 and their prices 105. The two databases 104, 105 could becombined into a single database. In addition, the information stored inthe two databases 104, 105 is expected to be continually evolving andcan be supplemented or revised with new data through automatic or manualupdates, which allows the analysis tool to model personal energy-relatedequipment that is new to the market and other kinds of changes.

Each listing in the equipment database 105 lists a type of equipment andthe type of fuel used, including, for example, electricity, heating gasor oil, gasoline (or diesel), or solar. The user makes selections ofequipment for both current and proposed personal equipment investments.Each equipment listing also includes energy-related characteristics,including classifying each listed equipment as affecting one or more ofpersonal electricity cost, heating cost, transportation cost, ormaintenance cost; and an energy affect that can be quantitativelyexpressed as measures of one or more of personal energy-consumption,energy-conservation, or (on-site) energy-production. For instance, anon-EV (electric vehicle) car consumes gasoline (or diesel) and theenergy affect can be expressed as average miles per gallon. The annualor periodic cost of fuel can thus be projected by multiplying annual orperiodic mileage by the average miles per gallon. Note that some typesof equipment neither consume nor produce energy, such as different kindsof building envelope investments, which indirectly conserve energy bypreventing infiltration of ambient conditions.

However, their energy-related affect can be indirectly expressed basedon insulative contributions to a building envelope, from which a cost(or savings) can be derived. As well, each equipment listing specifiesenergy-related and general characteristics that include, as applicable,name; model number; model year; fuel type: and energy (fuel)consumption, conservation or production characteristics, operationalparameters, and other related performance specifications. Equipmentinformation for energy investments that specifically affect buildingenvelope, furnace, and heat delivery and suitable for use in theequipment database 105 is described infra with reference to FIG. 12).Other equipment information could also be included in each listing. Theequipment database 105 can include:

-   -   1. Electricity-related equipment investments, including        lighting, appliances, and other devices that consume        electricity.    -   2. Building envelope equipment investments, including windows,        window shades, ceiling and wall insulation, radiant barriers,        roof ridge vents, and other fixtures that conserve energy within        a building envelope.    -   3. Space conditioning equipment investments, including natural        gas furnaces, air conditioning units, heat pumps, stand-alone        heaters, and other units that consume energy for space        conditioning.    -   4. Water heating equipment investments, which can either be        units that consume energy or conserve energy for heating water.    -   5. Vehicle and transportation equipment investments, which can        be conveyances or use of conveyances that consume energy for        transportation, conserve energy for transportation, or both, as        in the case of a hybrid automobile.    -   6. On-site energy producing equipment investments relating to        source of electricity, including photovoltaic power generation,        or, less commonly, small wind, small hydroelectric, or other        distributed or standalone power generation technologies, all of        which produce electricity.        Other types of equipment are possible.

Each listing of price in the equipment prices database 105 correspondsto a listing of equipment in the equipment database 105 and includes, asapplicable, cost of acquisition, whether by purchase, lease, rental, orother form; installation cost; maintenance cost; costs of ownership,such as annual registration, emissions compliance, and taxes; rebates,discounts, or other incentives; and, optionally, current valuation, suchas depreciated value, residual value, resale value, trade-in value, orsalvage value. Other price information could also be included.

Based upon the types of energy-related investments selected, up to threesets of current data 102 may be maintained. First, for all investments,electricity, fuel, and gasoline consumption data 106 are collected foreach equipment selection 101 for a recent time period, which willgenerally be for the past year. The consumption data 106 is formed intotime series, which is particularly important for electricity and fuel,specifically, fuel used for space conditioning and water heating. Thesource, quantity, and type of consumption data will depend upon thenature of the equipment selection. For instance, net electricityconsumption is available from power utility bills, although the amountof electricity consumed for a particular purpose, such as space or waterheating, would need to be identified or estimated from net consumption.Fuel consumption depends upon the form of delivery. Bulk fuels, such asheating oil, are delivered en masse to an on-site tank; for analysispurposes, consumption can be equated to amount purchased. Consumption ofmetered fuels, like natural gas, is also available from fuel bills and,like electricity, use for a specific purpose, may need to be identifiedor estimated, such as described supra with reference to Equation (10)for the case of fuel for space heating. Gasoline (or diesel) consumptioncan be estimated by dividing annual miles driven by average miles pergallon, or similar metric.

Second, when the proposed energy investments relate to changes to thebuilding's thermal envelope, the thermal characteristics 107 of thebuilding are collected. The overall thermal properties of a building(UA^(Total)) may already be available from an energy audit, or could bedetermined using the empirical approach described supra with referenceto FIG. 4.

Third, when the proposed energy investments relate to on-site energyproduction, historical solar resource, if photovoltaic energy productionis being considered, and weather data 108 are collected for the samerecent time period as the consumption data 106. In addition, ifnecessary, the historical solar resource and weather data 108 areconverted into time series using the same time resolution as applicableto the consumption data 106. Weather data can be obtained from weatherreporting services. Solar resource data is discussed in further detailinfra. The equipment selections 101 are combined with the current data102 to generate proposed data 103 for indicating annual consumption 109,by fuel type, which are calculated for both the equipment currently inuse and the equipment proposed for use to replace or upgrade the currentequipment. Fuel consumption and gasoline (or diesel) consumption areconverted into electricity-equivalent units, as further described infra.The electricity consumption time series data is submitted to a billcalculator 110 and is combined with electric rate structure informationto calculate an estimated annual cost 112. The estimated annual cost 112is combined with the electricity-equivalent units to forecast a totalannual cost, and the initial capital cost is compared to the totalannual cost to determine an estimated system payback 113.

From a non-technical person's perspective, a sufficient amount ofinformation is presented in a single screen to help a consumer in makinginformed energy investment decisions. FIG. 9 is a detail of the GUI 90of FIG. 7 showing, by way of example, an annotated graph 120 of powerconsumption. The x-axis 121 represents time. They-axis 122 representspower, expressed in kW. Both current power consumption 123 and proposedpower consumption 124 are depicted, respectively based on theelectricity demand profiles for the current and proposed investments.Proposed power consumption 124 reflects the effect of electric vehicle(“EV”) charging; operation of water and space heating pumps; efficiencyinvestments in the form of load reduction achieved by replacing existingconstant load, “Always On” electric devices with more energy efficientelectric devices and modifying operating schedule parameters; and fuelswitching from natural gas, supplemented with on-site photovoltaic powergeneration.

The effects current and proposed energy investments are ultimatelyreflected as a payback on investment, which helps provide a consumerwith both answers on personal energy consumption and an understandingwhat options and alternatives work best for the consumer's energy needs.FIG. 10 is a process flow diagram showing a routine 130 for evaluatingpotential energy investment payback for use in the method 100 of FIG. 8.The process uses the equipment selections 101 in combination, asapplicable, with current electricity, fuel, and gasoline consumptiondata 106; building thermal characteristics 107; and historical solarresource and weather data 108.

By way of example, potential energy investments that affect electricitycost (C^(E)), fuel for heating cost (C^(F)), and gasoline (or otherautomobile fuel) cost (C^(G)), per Equation (1), as discussed supra, aremodeled, but other costs, including maintenance cost (C^(M)), could alsobe weighed in the evaluation of total energy-related costs C^(Total).Initially, as applicable, an initial capital cost 135, as discussedsupra, and annual consumption, by fuel type, are calculated (step 131).The annual consumption values are determined for both the equipmentcurrently in use and the equipment proposed to replace or upgrade thecurrent equipment. In this example, the total energy-related costsC^(Total) include gasoline (or other automobile fuel) cost (C^(G)), sothe energy consumed by the person's mode of transportation isdetermined. This example assumes that the form of transportation is apersonal car. Other forms of transportation are possible, such astrains, buses, bikes, walking, and so forth.

TABLE 2 Vehicle Fuel Consumption Current Proposed Annual Mileage 12,00012,000 Miles Per Gallon 16 129 Vehicle Is Included In Analysis? TRUETRUE Gasoline Consumption (gallons per year) 750 93 Miles Per kWh 0.473.83 Electricity Consumption (kWh per year) 25,275 3,135 Vehicle IsElectric Powered? FALSE TRUE EV Charging Efficiency N/A 85% ElectricityPurchases (kWh-eq. per year) 25,275 3,688 Gasoline Purchases (gallonsper year) 750 0 Electricity Purchases (kWh per year) 0 3,688

Referring to Table 2, the consumer currently drives a 2004 Honda OdysseyEX minivan about 12,000 miles per year primarily for city driving. Forthis type of usage, the vehicle has a stated fuel economy of 16 milesper gallon and will consume 750 gallons of gasoline annually. There are33.7 kWh of energy per gallon of gasoline, so the vehicle's annual fuelconsumption represents an electricity-equivalent of 25,275 kWh annually.

The consumer is proposing to replace the current vehicle with a 2013Nissan Leaf SV, which is plug-in charging all-electric vehicle. The LeafSV achieves a gasoline-equivalent of 129 miles per gallon for citydriving, which converts to 3.8 miles per kWh. An inefficiency occurswhen the vehicle is charged, which can be assumed to be around 15percent. For the same type of usage, about 12,000 miles per yearprimarily for city driving, the Leaf SV, at 3.8 kWh per mile with an 85percent charging efficiency, would require 3,688 kWh annually, whichcompares quite favorably to the electricity-equivalent of 25,275 kWhused by the Odyssey EX under identical driving conditions.

Electric energy efficiency investments reduce annual electricityconsumption. In every building, there is typically some percentage ofelectricity drawn on a continuous basis by devices that are alwaysturned on. These constant load devices may be, for example, electric hotwater heaters, clocks, electric timers for operating lights,uninterruptible power supplies for computer equipment, and appliancesplaced on a standby mode.

The electric load consumed by “Always On” devices can be reduced byreplacing existing “Always On” electric devices with more energyefficient electric devices and modifying operating schedule parametersor by unplugging unused devices. Referring to Table 3, a reduction in“Always On” loads from 150 Watts to 50 Watts translates to a savings of876 kWh per year [(0.15 kW−0.05 kW)×8,760 hours].

In addition, other electric efficiency investments are possible, such asenergy efficient appliances and efficient lighting. In this example,replacing fifty 15-Watt CFLs with 6-Watt LEDs that are operated for onlysix hours per day translates to a savings of 986 kWh per year [50×(0.015kW−0.006 kW)×(6 hours per day)×(365 days per year)].

TABLE 3 Electrical Efficiency Sayings and Capital Cost Savings (kWh/yr)Savings (kWh/hour) Cost Always On Loads 876 0.10  $0 Lights 986 0.11$250 Total 1,862 0.21 $250

Improvements to a building can change the overall thermal performance ofthe building UA^(Total). Improvements can affect how heat loss or gainoccurs by conduction through each unique building surface and throughinfiltration. In Equation (42), as further described infra, theseeffects can be calculated by incrementally changing the building'sthermal characteristics. Referring to Table 4, the house in this examplehas R-6 wall insulation, that is, insulation with an R-value of 6.Adding R-13 insulation increases the overall insulation to R-19. Thechange in UA^(Total) for 225 ft² of R-19 insulation equals 26 Btu/hr-°F. [(⅙− 1/19)×225]. The total of all UA^(Total) changes equals 218Btu/hr-° F.

Several ratios are calculated based on current and proposed efficienciesand UA^(Total) values, as further discussed infra with reference toEquation (38), Equation (42), and Equation (43). Referring to Table 5,the efficiency ratio equals the current value divided by the proposedvalue. The relationship is reversed for the UA^(Total) values, where theUA^(Total) ratio equals the proposed UA^(Total) value divided by thecurrent UA^(Total) value. The current UA^(Total) value of the buildingis a required input and can be obtained by the empirical approachdescribed supra with reference to FIG. 4. The efficiency ratios in Table5 will now be discussed.

The Water Heating Energy Factor Ratio is used to determine the proposedtotal annual energy required for water heating. Current annual waterheating fuel consumption was calculated using the approach summarized inEquation (12), which is 199 therms of natural gas. There are 3,412 Btuper kWh. Thus, the current consumption of fuel for water heating can beexpressed as 5,820 kWh of natural gas. The proposed consumption of fuelfor water heating equals 5,820 kWh times the Water Heating Energy FactorRatio and is 1,473 kWh per year (5,820×0.25). Referring to Table 6, theinstalled cost for the heat pump water heater is $1,899.

TABLE 6 Water Heating Capital $1,199 Installation $700 Total Cost $1,899

Space heating requirements are calculated in a two-step process. Thesizing of the heating source is first estimated, after which cost can bedetermined. One approach to sizing the heating source is provided inManual J, cited supra. However, that sizing approach does not take intoaccount historical information about the building's consumption nor isthe sizing approach dynamic.

Here, an alternate approach to sizing of the heating source is applied.First, historical fuel consumption requirements are evaluated todetermine worst-day situations, rather than simply assuming worst dayconditions. Second, the approach dynamically incorporates the effect ofinvestment decisions across technologies and fuel types and theirvarious interactions. For example, the decision to add insulating windowshades reduces a building's rate of heat loss and thus reduces therequired size of the space conditioning heat pump, which, in turn,reduces capital cost. This decision also reduces the total amount ofheat that needs to be provided by the heat pump, which, in turn, reducesthe size of the photovoltaic system needed to supply energy to the heatpump. These interactions are automatically calculated.

Referring to Table 7, the maximum daily natural gas purchased for thebuilding in this example for space heating purposes, as determined usingdaily water heating consumption from Equation (12) combined with totaldaily natural gas purchases, was 5.71 therms. In other words, the peakday over the year analyzed required a purchase of 5.71 therms of naturalgas. Based on the proposed energy investments, the building envelope andduct losses will respectively be lowered to 63 percent and 82 percent,per Table 5. The product of these two ratios is 51 percent, which meansthat proposed energy investments would require 2.93 therms on the worstday, assuming the same furnace efficiency, η^(Furnace). 48,836 Btu ofnatural gas must be purchased per hour, given a maximum daily operationof six hours. Since the current furnace is 80 percent efficient, 39,069Btu of heat are actually delivered per hour.

The proposed space heating source is a heat pump that has a HeatingSeason Performance Factor (HSPF) of 8.5 Btu/Wh, which means that theheat pump will consume 4.6 kW per hour (39,069 Btu/8,500 Btu/kWh). Therating of this heat pump can also be expressed in tons by dividing by12,000. The cost for the heat pump equals the product of the rating,expressed in in tons, times the cost, expressed in dollars per ton, plusthe fixed cost, installation cost, and ductwork cost. The total proposedspace heating cost is $11,256.

TABLE 7 Space Heating Sizing UA Ratio * Current Duct Ratio Proposed MaxDaily Consumption 5.71 51% 2.93 (therms/day) Max Daily Operation 6 6(Hours) Max Hourly Operation 95,242 48,836 (Btu/hour) Delivered Heat(Btu/hour) 76,193 39,069 Furnace HSPF (Btu/Wh) 8.50 Furnace AFUE 0%Furnace Is Heat Pump TRUE Max Hourly Space Heating 4.60 Consumption(kW/hr) Max Hourly Space Heating 3.26 Consumption (tons) Space HeatingCost Required Tons Cost per Ton Cost Capacity Cost 3.26 $1,000 $3,256Fixed Cost $3,000 Capacity + Fixed Cost $6,256 Installation Cost $2,000Duct Cost $3,000 Total Cost $11,256 

Installing a photovoltaic system allows a consumer to offset purchasedelectricity consumption with on-site power generation. In theinteractive energy investment choices analysis tool, the consumer couldsimply explicitly size the photovoltaic system. Alternatively, theconsumer can specify the percentage of purchased electricity consumptionto offset by on-site power generation.

Referring to Table 8, in this example, annual consumption is estimatedat 9,682 kWh. The consumer has indicated that the photovoltaic systemshould provide 80 percent of annual consumption, or 7,746 kWh.Historical photovoltaic power production was analyzed for the locationand time period of interest. Here, a 1-kW-DC, south-facing photovoltaicsystem would produce 1,521 kWh per year; however, a 5.09 kW-DCphotovoltaic system is needed to produce 7,746 kWh. A photovoltaicsystem of this capacity would cost $20,376 and would be eligible toreceive 30-percent federal tax credit of $6,113.

TABLE 8 PV System Sizing and Cost Proposed Consumption (kWh/yr)  9,682Percent Cons, to be Supplied by PV 80% PV Supplied Energy (kWh/yr) 7,746 Historical Production (kWh/kW-DC/yr)  1,521 Required PV Size(kW-DC)     5.09 Per Unit PV Cost ($/kW)  $4,000 Total PV Cost $20,376Federal Tax Credit  $6,113

Referring back to FIG. 10, annual electric consumption is then convertedinto time series consumption (step 132), which allocates annual electricconsumption into time-series values on an hourly, or other timeinterval, basis. For any particular end-use, the distribution of annualenergy must satisfy the requirement that the sum of all 8,760 hours in ayear (or all 8,784 hours in a leap year), as factored, equals 1, inaccordance with:

$\begin{matrix}{{\sum\limits_{m = 1}^{12}{\sum\limits_{d = 1}^{28\mspace{11mu} {to}\mspace{11mu} 31}{\sum\limits_{h = 1}^{24}{hf}_{m,d,h}}}} = 1} & (32)\end{matrix}$

where m, d, and h respectively represent month, day, and hour; and hfrepresents the percent of total annual energy being consumed in a givenhour. A daily factor for each month and day is defined, such that thesum of the daily factors for a particular month and day equals:

$\begin{matrix}{{df}_{m,d} = {\sum\limits_{{Hour} = 1}^{24}{hf}_{{hm},d}}} & (33)\end{matrix}$

where hf_(h|m,d) signifies the hourly factor for hour h, given month mand day d.

A new term, called normalized hourly factors, is defined, which equalsthe original hourly factor divided by the daily factor for that monthand day, expressed as:

$\begin{matrix} & (34)\end{matrix}$

Rearranging Equation (34) and substituting into Equation (32) yields:

∑ m = 1 12  ∑ d = 1 28   to   31  df m , d  ∑ h = 1 24  | m , d= 1 ( 35 )

Repeat the same process to define a daily factor/monthly factorrelationship:

∑ m = 1 12  mf m  ∑ d = 1 28   to   31  | m   ∑ h = 1 24  | m, d = 1 ( 36 )

The benefit of Equations (35) and (36) is that they can be used tocreate load profiles for which detailed hourly data is unavailable.Suppose, for example, that total daily water heating consumption isavailable for each day of the year, but hourly data are unavailable. Inthis case, the consumption profiles distribution within any given day ofthe year could be assumed to be the same as every other day, as would bethe case if the status of the water heater was always either on or offduring the same time of the day. This assumption does not require thatthe total water heater load be the same for every day of the year.

Here, Equation (35) simplifies to the following equation:

$\begin{matrix}{{\sum\limits_{m = 1}^{12}{\sum\limits_{d = 1}^{28\mspace{14mu} {to}\mspace{14mu} 31}{{df}_{m,d}{\sum\limits_{h = 1}^{24}}}}} = 1} & (37)\end{matrix}$

Equation (37) can be used in the context of current Green Button naturalgas data. A similar approach can be taken to define constant loadprofiles for a day within a given month.

The hourly distribution factors for a proposed energy investmentscenario can be depicted. FIG. 11 is a graph depicting, by way ofexample, assumed hourly distribution factors, as determined by theroutine of FIG. 10. The x-axis represents time of day. The y-axisrepresents percentage. The assumed hourly distribution factors in theexample for water heating, space heating, and electric vehicle chargingare used in this example. Electric vehicle charging is assumed to followthe same pattern every day of the year. The daily factors for the waterand space heating are based on measured natural gas purchase data. Table9 presents projected hourly electricity consumption by end-use for oneday. The columns present electricity by Other Consumption, WaterHeating, Space Heating, and EV Charging. The sum of these four columnsis Total Consumption.

TABLE 9 Projected Hourly Electricity (kWh) Rate Structure Other WaterSpace EV Total PV Net Information DST Start Time Consumption HeatingHeating Charging Consumption Production Consumption Season Period RateCost 1/1/13 12:00 AM 0.32 0.00 0.0 2.02 2.34 0.00 2.34 Winter Off Peak$0.10 $0.24 1/1/13 1:00 AM 0.42 0.00 0.0 2.02 2.44 0.00 2.44 Winter OffPeak $0.10 $0.25 1/1/13 2:00 AM 0.85 0.00 0.0 2.02 2.87 0.00 2.87 WinterOff Peak $0.10 $0.29 1/1/13 3:00 AM 0.87 0.00 0.0 2.02 2.89 0.00 2.89Winter Off Peak $0.10 $0.29 1/1/13 4:00 AM 0.85 0.00 0.0 2.02 2.87 0.002.87 Winter Off Peak $0.10 $0.29 1/1/13 5:00 AM 0.85 0.00 2.1 0.00 2.930.00 2.93 Winter Off Peak $0.10 $0.30 1/1/13 6:00 AM 1.21 1.35 2.1 0.004.64 0.00 4.64 Winter Off Peak $0.10 $0.47 1/1/13 7:00 AM 0.85 1.35 2.10.00 4.28 −0.21 4.08 Winter Partial Peak $0.16 $0.66 1/1/13 8:00 AM 1.140.00 2.1 0.00 3.22 −0.98 2.25 Winter Partial Peak $0.16 $0.37 1/1/139:00 AM 0.83 0.00 0.0 0.00 0.83 −1.94 −1.11 Winter Partial Peak $0.16($0.18) 1/1/13 10:00 AM 0.52 0.00 0.0 0.00 0.52 −2.63 −2.12 WinterPartial Peak $0.16 ($0.35) 1/1/13 11:00 AM 0.22 0.00 0.0 0.00 0.22 −3.01−2.79 Winter Partial Peak $0.16 ($0.46) 1/1/13 12:00 PM −0.18 0.00 0.00.00 −0.18 −3.07 −3.25 Winter Partial Peak $0.16 ($0.53) 1/1/13 1:00 PM−0.32 0.00 0.0 0.00 −0.32 −2.81 −3.13 Winter Partial Peak $0.16 ($0.51)1/1/13 2:00 PM −0.13 0.00 0.0 0.00 −0.13 −2.21 −2.35 Winter Peak $0.27($0.63) 1/1/13 3:00 PM 1.18 0.00 0.0 0.00 1.18 −1.41 −0.23 Winter Peak$0.27 ($0.06) 1/1/13 4:00 PM 2.11 0.00 0.0 0.00 2.11 −0.48 1.62 WinterPeak $0.27 $0.43 1/1/13 5:00 PM 1.29 1.35 0.0 0.00 2.64 0.00 2.64 WinterPeak $0.27 $0.71 1/1/13 6:00 PM 1.60 0.00 2.1 0.00 3.68 0.00 3.68 WinterPeak $0.27 $0.99 1/1/13 7:00 PM 1.96 0.00 2.1 0.00 4.04 0.00 4.04 WinterPeak $0.27 $1.08 1/1/13 8:00 PM 0.24 0.00 0.0 0.00 0.24 0.00 0.24 WinterPeak $0.27 $0.06 1/1/13 9:00 PM 0.33 0.00 0.0 0.00 0.33 0.00 0.33 WinterPartial Peak $0.16 $0.05 1/1/13 10:00 PM 0.35 0.00 0.0 0.00 0.35 0.000.35 Winter Partial Peak $0.16 $0.06 1/1/13 11:00 PM 0.72 0.00 0.0 0.000.72 0.00 0.72 Winter Off Peak $0.10 $0.07

Referring back to FIG. 10, net consumption is calculated usingtime-correlated production data (step 133), which requires combiningtime series total consumption data with time- and location-correlatedproduction data. In many cases, photovoltaic production data may be ofinterest. As a result, historical photovoltaic production data needs tobe simulated for the location of interest. The simulation must beperformed using time- and location-correlated solar resource data, aswell as specific information about the orientation and othercharacteristics of the photovoltaic system, such as can be provided bythe Solar Anywhere service (http://www.SolarAnywhere.com), a Web-basedservice operated by Clean Power Research, L.L.C., Napa, Calif. The timeseries photovoltaic production data is subtracted from the time seriesconsumption data to yield time series net consumption data. Photovoltaicproduction and net consumption for one day are presented in Table 9.

Referring finally back to FIG. 10, an electric bill is calculated (step134), from which annual cost 136 can be forecast and upon which payback137 can be determined. Electric bill calculation involves combining thenet consumption data with the applicable electric rate structureinformation, including details about fixed, demand, tier, andtime-of-day charges. In Table 9, the right columns present results forone day using a Pacific Gas and Electric EV-A tariff rate structure.Importantly, different rates can be used for “Before” and “After”calculations because a rate switch may be financially beneficial. Thenet consumption profile should be run through the detailed electric billcalculator for all possible rate structures to select the one thatprovides the greatest benefit.

The interactive energy investment choices analysis tool, described suprawith reference to FIG. 7, provides a consumer with the informationnecessary to evaluate the economic savings or costs of newenergy-related equipment investments for existing buildings. In asimilar manner, energy investments that specifically affect buildingenvelope, furnace, and heat delivery can also be evaluated. FIG. 12 is aflow diagram showing a computer-implemented method for evaluatingpotential energy investment scenarios specially affecting a building'senvelope, heating source, or heating delivery 140, in accordance with afurther embodiment. The method 140 can be implemented in software andexecution of the software can be performed on a computer system, such asfurther described infra with reference to FIG. 14, as a series ofprocess or method modules or steps.

Initially, the amount of total fuel purchased annually Q^(F) isobtained, which can be found in a utility bill, and the ratio H of theamount of fuel consumed annually for heating Q^(F-Heating) over theamount of the total fuel purchased annually Q^(F) is calculated (step141). The amount of fuel consumed annually for heating Q^(F-Heating) canbe derived empirically based on the fuel consumed during non-heatingseason months, as described supra with reference to Equation (2), orfrom the building's thermal performance and heating and deliveryequipment characteristics, as described supra with reference to Equation(14) (step 141). The ratio H can be used to identify the initial cost145 of the fuel consumed annually for heating based on the total cost ofthe fuel purchased annually.

To evaluate energy investments mainly affecting heating efficiency ordelivery efficiency, a modified version of Equation (10) can be used.Depending upon the energy investments being evaluated, one or more ofthe existing thermal performance of the building UA^(Total), existingfurnace efficiency η^(furnace), and existing delivery efficiencyη^(delivery) may be needed and can be estimated, if not available (step142). To represent the costs after investment, each variable in Equation(10) that corresponds to a new energy investment is labeled with a caretsymbol (̂) (step 143). Equation (15) is substituted into the Equation(10), which is then simplified and solved (step 144) to yield the newamount of fuel used strictly for space heating {circumflex over(Q)}^(F-Heating):

Q ^ F  -  Heating = ( H )  ( Q F )  ( Total UA Total )  ( η furnaceη ^ furnace )  ( η delivery η ^ delivery ) ( 38 )

Note that the variables in Equation (15) do not have caret symbolsbecause the variables represent the values for the existing buildingbefore the investment is made. Based on {circumflex over(Q)}^(F-Heating), the new cost 146 of the fuel consumed annually forheating based on the new energy-related equipment investments can befound, and the investment payback 147 can be evaluated by comparing theinitial cost 145 to the new cost 146.

In Equation (38), the new amount of fuel required for heating{circumflex over (Q)}^(F-Heating) equals the amount of total fuelpurchased annually Q^(F), as fractionally adjusted by the ratio H,multiplied by three additional interrelated ratios, each term in theratio representing, as applicable, characteristics of both existing andproposed equipment:

-   -   New thermal performance of building        ^(Total) divided by existing thermal performance of building        UA^(Total).    -   Existing furnace efficiency η^(furnace) divided by new furnace        efficiency {circumflex over (η)}^(furnace).    -   Existing delivery efficiency η^(delivery) divided by new        delivery efficiency {circumflex over (η)}^(delivery).        Equation (38) is quite useful. For example, suppose that a        consumer is considering an investment in a new furnace. The        existing furnace has an 80-percent efficiency η^(furnace) and        the delivery system has a 78-percent efficiency η^(delivery). If        the building had a $1,000 annual bill for fuel required for        heating, Equation (38) allows the consumer to determine the fuel        cost for a new 96-percent efficient furnace with 95-percent        efficient ductwork. Since there is no change to the building's        thermal characteristics, Equation (38) suggests that the new        annual fuel cost will be $1,000×(0.80/0.96)×(0.78/0.95)=$684.

In addition to assessing the benefits associated with a new furnace anddelivery system, a consumer may want to understand the effect ofbuilding envelope improvements, such as new windows or increasedinsulation, which can be determined by evaluating both the building'soriginal thermal characteristics (UA^(Total)) and its new thermalcharacteristics (

^(Total)). The typical approach to obtaining the existing and newthermal characteristics of a building is to perform a detailed energyaudit that requires fully modeling the building by taking physicalmeasurements of the surface areas of all non-homogeneous exterior-facingsurfaces or verifying non-exposed surfaces. Once calculated, theexisting UA^(Total) is then parametrically adjusted to quantify newthermal characteristics.

Although comprehensive and customized to a specific building underconsideration, there are notable weaknesses to energy audits. First,energy audits can be quite expensive, costing over a thousand dollarsfor the pre- and post-inspections and the filing of the necessarypaperwork to obtain utility rebates. Second, equipment problems duringtesting can require multiple site visits. Third, energy audit resultsbecome less valid as new energy investments are made, which change thebaseline thermal characteristic findings.

Consider an alternative method. Assume that the original overall thermalcharacteristic UA^(Total) of a building is known. UA^(Total) can bedetermined, for instance, using the empirical approach described suprawith reference to FIG. 4. Suppose that energy investments are made foronly one portion of the building that only affect heat transfer throughthe building envelope due to conduction. For example, the building owneris considering an investment in new windows, which can be called thej^(th) surface area. The new thermal characteristics of the building

^(Total) equal the original building characteristics UA^(Total), minusthe thermal characteristics of the original windows, plus the thermalcharacteristics of the new windows, which can be expressed as:

^(Total) =UA ^(Total)−(U ^(j) A ^(j) −Û ^(j) A ^(j))=UA ^(Total)−(U ^(j)−Û ^(j))A ^(j)  (39)

where U^(j) and Û^(j) respectively represent the existing and proposedU-values of surface j, and A^(i) represents the surface area of surfacej.

Equation (39) can be restated in a generalized form when there are Minvestments being made in a building:

Total = UA Total + ∑ j = 1 M  ( U j - U ^ j )  A j ( 40 )

Suppose further that energy investments are made that affect heat lossesdue to infiltration. As discussed supra with reference to Equation (18),infiltration losses are based on the density of air (ρ), specific heatof air (c), number of air changes per hour (n), and volume of air perair change (V). The volume of a building can be approximated bymultiplying building square footage by average ceiling height. Equation(40) can be modified to account for “Before” and “After” infiltrationheat transfer:

$\begin{matrix} & (41)\end{matrix}$

Substituting Equation (41) into Equation (38):

$\begin{matrix}{{\hat{Q}}^{F\text{-}{Heating}} = {(H)\left( Q^{F} \right)\left( {1 - \frac{{\sum\limits_{j = 1}^{M}{\left( {U^{j} - {\hat{U}}^{j}} \right)A^{j}}} + {\rho \; {c\left( {n - \hat{n}} \right)}V}}{{UA}^{Total}}} \right)\left( \frac{\eta^{furnace}}{{\hat{\eta}}^{furnace}} \right)\left( \frac{\eta^{delivery}}{{\hat{\eta}}^{delivery}} \right)}} & (42)\end{matrix}$

Equation (42) implies that only the following information is required toquantify the energy impact of building envelope investments:

-   -   Percentage of fuel bill used for heating purposes (H), which can        be obtained from monthly fuel bill data.    -   Existing fuel bill (Q^(F)), which can be obtained from the local        utility bill records.    -   Existing overall thermal properties of building (UA^(Total)),        which can be determined using the empirical approach described        supra with reference to FIG. 4.    -   Existing furnace efficiency (η^(furnace)). This value is based        on manufacturer and furnace model and is often listed directly        on the furnace chassis or manufacturer specifications.    -   New furnace efficiency ({circumflex over (η)}^(furnace)). This        value is based on manufacturer and furnace model and is often        listed directly on the furnace chassis or manufacturer        specifications.    -   Existing delivery system efficiency (η^(delivery)). This value        typically ranges between 70 and 95 percent. η^(delivery) can be        estimated or can be measured directly using a duct blast (or        duct leakage) test, which is a detailed, on-site test.        Alternatively, delivery system efficiency can be measured        empirically using temperature tests in the spaces in which the        ducts are located.    -   New delivery system efficiency ({circumflex over        (η)}^(delivery)). This value can be specified as a requirement        as part of ductwork replacement. Verification involves a        detailed, on-site test.    -   Areas of building surfaces to be replaced or upgraded. These        values can be determined using a tape measure and a calculator,        or software.    -   Existing U-values of thermal properties of building surfaces to        be replaced or upgraded. These values can be estimated.    -   New U-values of thermal properties of building surfaces to be        replaced or upgraded. These values are reported by the surface        manufacturer.    -   Number of air changes before and after energy investment. This        number is required for energy investments that affect        infiltration, but not for many other building        envelope-implicating energy investments. Verification involves a        detailed, on-site test.        The foregoing parameters are substituted into Equation (42)        (step 143), which is then simplified (step 144) to find the        annual cost 146 and payback 147.

In some special cases, Equation (42) can be simplified to:

$\begin{matrix}{{\hat{Q}}^{F\text{-}{Heating}} = {(H)\left( Q^{F} \right)\left( {1 - \frac{\left( {U^{j} - {\hat{U}}^{j}} \right)A^{j}}{{UA}^{Total}}} \right)}} & (43)\end{matrix}$

which applies when the heating source is not being replaced, thedelivery system is not being upgraded, the investment does not affectthe number of air changes per hour, or there is only one investmentunder consideration. Similar to Equation (42), the foregoing parametersare substituted into Equation (43) (step 143), which is then simplified(step 144) to find the annual cost 146 and payback 147.

Consider two examples that show how Equation (43) can be used. In bothexamples, assume that the buildings overall thermal performanceUA^(Total) is 800, the natural gas bill is $1,000 annually, 60 percentof the natural gas consumed is for heating, and that natural gas costs$1 per therm.

Example: A homeowner is considering a $10,000 investment to upgradesingle-pane windows with an R-value of 0.8 to triple-pane, low-e, argongas-filled windows with an R-value of 6.7. The homeowner has 300 ft² ofwindows. How much would the homeowner save on heating?

The homeowner currently purchases 1,000 therms per year of natural gasbased on an annual heating bill of $1,000 and natural gas price of $1per therm. Assuming that 400 therms are for non-heating purposes,leaving 600 therms for heating. According to Equation (43), the newheating fuel consumption will be:

$\begin{matrix}{{\hat{Q}}^{F\text{-}{Heating}} = {{(0.6)\left( {1,000} \right)\left( {1 - \frac{\left( {\frac{1}{0.8} - \frac{1}{6.7}} \right)300}{800}} \right)} = {352\mspace{14mu} {therms}}}} & (44)\end{matrix}$

The $10,000 investment will save the homeowner $248 per year($1/therm)×(600 therms−352 therms).

Example: The same homeowner decided to look into a different energyinvestment. The home currently has a 2,500 ft² ceiling with R-6insulation. The homeowner is considering spending $1,000 to upgrade toR-30 insulation. According to Equation (43), the new heating fuelconsumption will be:

$\begin{matrix}{{\hat{Q}}^{F\text{-}{Heating}} = {{(0.6)\left( {1,000} \right)\left( {1 - \frac{\left( {\frac{1}{6} - \frac{1}{30}} \right)2,500}{800}} \right)} = {350\mspace{14mu} {therms}}}} & (45)\end{matrix}$

This $1,000 investment will save the homeowner $250 per year($1/therm)×(600 therms−350 therms).

Note that Equation (38), Equation (42), and Equation (43) can all beused in the evaluation of energy investments affecting buildingenvelope, furnace, and heat delivery. Choosing the appropriate equationdepends upon the form of energy investment under consideration. FIG. 13is a process flow diagram showing a routine for selecting energyinvestment scenario parameters 150 for use in the method 140 of FIG. 12.In all three cases, the annual payback 147 on fuel savings for spaceheating from proposed energy investments can be determined. However,depending upon the energy investment, different parameters are requiredand, in some cases, a simpler form of evaluation by choosing an equationrequiring fewer parameters might be used (step 151). If the proposedenergy investments mainly affect heating efficiency or deliveryefficiency (step 152), Equation (38) is the most appropriate form ofevaluation. If the proposed energy investments only affect heat transferdue to conduction through only one portion of a building, Equation (42)is better suited to the task. Finally, when the heating source is notbeing replaced, the delivery system is not being upgraded, theinvestment does not affect the number of air changes per hour, or thereis only one investment under consideration, Equation (43) can be used.

Fractionally inferring the percentage of the total fuel purchased forspace heating purposes, as described supra with reference to FIG. 2;empirically estimating overall thermal performance of a building througha short-duration controlled test, as described supra with reference toFIG. 4; evaluating potential energy investment scenarios, as describedsupra with reference to FIG. 10; and evaluating new energy investmentsspecifically affecting building envelope, heating source, or heatingdelivery, as described supra beginning with reference to FIG. 12, can beperformed with the assistance of a computer, or through the use ofhardware tailored to the purpose. FIG. 14 is a block diagram showing acomputer-implemented system 160 for empirically estimating overallthermal performance of a building through a short-duration controlledtest, in accordance with one embodiment, which can also be used forfractionally inferring the percentage of the total fuel purchased forspace heating purposes and evaluating potential energy investmentscenarios. A computer system 161, such as a personal, notebook, ortablet computer, as well as a smartphone or programmable mobile device,can be programmed to execute software programs 162 that operateautonomously or under user control, as provided through user interfacingmeans, such as a monitor, keyboard, and mouse. The computer system 161includes hardware components conventionally found in a general purposeprogrammable computing device, such as a central processing unit,memory, input/output ports, network interface, and non-volatile storage,and execute the software programs 162, as structured into routines,functions, and modules. In addition, other configurations ofcomputational resources, whether provided as a dedicated system orarranged in client-server or peer-to-peer topologies, and includingunitary or distributed processing, communications, storage, and userinterfacing, are possible.

The computer system 161 remotely interfaces to a heating source 166 anda thermometer 167 inside a building 163 that is being analyticallyevaluated for overall thermal performance UA^(Total). In a furtherembodiment, the computer system 161 also remotely interfaces to athermometer 168 outside the building 163, or to a remote data sourcethat can provide the outdoor temperature. The computer system 161 cancontrol the heating source 166 and read temperature measurements fromthe thermometer 167 throughout the short-duration controlled test,during which the baseline indoor temperature T₀, the starting indoortemperature T₁, and the final indoor temperature T₃ are recorded. In afurther embodiment, a cooling source (not shown) can be used in place ofor in addition to the heating source 166. The expected final indoortemperature T₃ ^(No Heat) is also estimated by the computer system 161,based on a projection of what the indoor temperature would have been atthe end of the test, had the heating source not been turned back on. Thecomputer system 161 executes a software program 162 to determine overallthermal performance UA^(Total) based on the empirical approach describedsupra with reference to FIG. 4.

In a further embodiment, the computer system 161 may be remotelyinterfaced with a server 170 operated by a power utility or otherutility service provider 171 over a wide area network 169, such as theInternet, from which fuel purchase data 172 can be retrieved. Thecomputer system 161 executes a software program 162 to fractionallyinfer the percentage of the total fuel purchased for space heatingpurposes, as described supra with reference to FIG. 2.

In a still further embodiment, the UA^(Total) can be used as part of thebuilding thermal characteristics. Optionally, the computer system 161may also monitor electricity 164 and other metered fuel consumption,where the meter is able to externally interface to a remote machine, aswell as monitor on-site power generation, such as generated by aphotovoltaic system 165. The monitored fuel consumption and powergeneration data can be used to create the electricity, fuel, andgasoline consumption data 96 and historical solar resource and weatherdata 98. The computer system 161 executes a software program 162 toevaluate potential energy investment scenarios, and provide a paybackestimate 137, as described supra with reference to FIG. 10.

In a yet further embodiment, the computer system 161 includes a storagedevice within which is stored one or more of the following data: thepercentage of fuel bill used for heating purposes, an existing fuelbill, existing overall thermal properties UA^(Total) of the building163, existing furnace efficiency, new furnace efficiency, existingdelivery system efficiency, new delivery system efficiency, areas ofbuilding surfaces to be replaced or upgraded, existing U-values ofthermal properties of building surfaces to be replaced or upgraded, newU-values of thermal properties of building surfaces to be replaced orupgraded, and number of air changes before and after energy investment.The computer system 161 executes a software program 162 to evaluate newenergy investments specifically affecting building envelope, heatingsource, or heating delivery, and provide a payback estimate 147, asdescribed supra with reference to FIG. 12.

While the invention has been particularly shown and described asreferenced to the embodiments thereof, those skilled in the art willunderstand that the foregoing and other changes in form and detail maybe made therein without departing from the spirit and scope.

What is claimed is:
 1. A system for empirical-test-based estimation ofoverall thermal performance of a building the aid of a digital computer,comprising: a non-transitory computer readable storage medium comprisingprogram code; a heating source comprising a heating element and aheating delivery component comprised inside a building; a thermometercomprised inside the building; a thermometer located outside of thebuilding; a computer processor interfaced to the storage medium andremotely interface, the heating source, the inside thermometer, and theoutside thermometer, wherein the computer processor is configured toexecute the program code to perform steps to: stop operation of theheating source at the beginning of an unheated period after recordinginto the storage medium a baseline indoor temperature from the indoorthermometer and a baseline outdoor temperature from the outdoorthermometer; temporarily resume operation of the heating source at theend of the unheated period after recording into the storage medium astarting indoor temperature from the indoor thermometer; stop operationof the heating source after running the heating source for a heatedperiod and record into the storage medium a final indoor temperaturefrom the indoor thermometer after a stabilizing period following theheated period; measure energy consumed in the building from thebeginning of the unheated period to the ending of the stabilizing periodas equaling heat gained inside the building from internal sources ofheat; estimate an expected final indoor temperature at the end of thestabilizing period based on the heating source not having been run forthe heated period; determine the heat gained inside the building overthe heating period through operation of the heating source using thefuel requirements of the heating source, the efficiency of the heatingsource, and the efficiency of the heating delivery component; estimateoverall thermal performance of the building using the heat gainedthrough using the heating source, the measured energy, the indoortemperatures, the baseline outdoor temperature, and the estimated finalindoor temperature.
 2. A system according to claim 1, wherein the heatgained inside the building by the heating source having been run for theheated period is determined in accordance with:$Q^{{Heat}\mspace{14mu} {Delivered}\text{-}{Furnace}} = {\left( R^{Furnace} \right)\left( {\eta^{Furnace}\eta^{Delivery}} \right)\left( {t_{2} - t_{1}} \right)\left( \frac{T_{0} - T_{3}^{{No}\mspace{14mu} {Heat}}}{T_{3} - T_{3}^{{No}\mspace{14mu} {Heat}}} \right)}$where Q^(Heat Delivered-Furnace) is the heat gained inside the buildingby the heating source having been run for the heated period, R^(Furnace)are the fuel requirements of the heating source, η^(Furnace) is theefficiency of the heating source, η^(Delivery) is the efficiency of theheating delivery component, t₁ is the starting time of the heatedperiod, t₂ is the ending time of the heated period, T₀ is the baselineindoor temperature, T₃ is the final indoor temperature, T₃ ^(No Heater)is the expected final indoor temperature, Δt is the unheated period fromtime t₀ to time t₁.
 3. A method according to claim 1, wherein the fuelrequirements Q_(F-Heating) of the heating source is determined inaccordance with:$Q^{F\text{-}{Heating}} = \frac{\left( {UA}^{Total} \right)(24)\left( {HDD}_{Location}^{{Set}\mspace{14mu} {Point}\mspace{14mu} {Temp}} \right)\left( {1 - {SSF}} \right)}{\eta^{Furnace}\eta^{Delivery}}$where UA^(Total) is the building thermal performance, HDD_(Location)^(Set Point Temp) represents the number of degree days when the outdoortemperature exceeds the desired Set Point temperature, η^(Furnace) isthe efficiency of the heating source, η_(Delivery) is the efficiency ofthe heating delivery component, and SSF represents the amount of energydelivered to a building by solar gains.
 4. A system according to claim1, wherein the computer processor is further configured to execute theprogram code to perform steps to: use the overall thermal performance ofthe building to analyze one or more potential energy investments intothe building, wherein at least one of the energy investments isperformed based on the analysis.
 5. A system according to claim 4,further comprising: a meter interfaced to the computer processor andconfigured to provide data associated with the building to the computerprocessor, wherein the computer processor further uses the provided datato evaluate the one or more energy investment for the building.
 6. Asystem according to claim 1, wherein the data comprises one or more ofelectricity consumption associated with the building, fuel consumptionassociated with the building, and photovoltaic power generation data bya photovoltaic power generation plant interfaced to the building.
 7. Asystem according to claim 1, wherein the computer processor is furtherconfigured to execute the program code to perform steps to: record intothe storage medium the outdoor temperature at one or more additionaltime points from the outdoor thermometer between the beginning of theunheated period and the end of the stabilizing period; and average thebaseline outdoor temperature and one or more of the outdoor temperaturestaken at one or more of the additional time points, wherein the averagedoutdoor temperature is used to estimate the overall thermal performanceof the building.
 8. A system according to claim 1, wherein the heatedperiod is during morning hours before a rising of the sun.
 9. A systemaccording to claim 1, further comprising: a cooling source that iscomprised within the building and that is interfaced to the computerprocessor, the computer processor further configured to execute theprogram code to perform steps to: stop operation of the cooling sourceat the beginning of an uncooled period after recording into the storagemedium a further baseline indoor temperature from the indoor thermometerand a further baseline outdoor temperature from the outdoor thermometer;temporarily resume operation of the cooling source at the end of theuncooled period after recording into the storage medium a furtherstarting indoor temperature from the indoor thermometer; and stopoperation of the cooling source after running the cooling source for acooled period and record into the storage medium a further final indoortemperature from the indoor thermometer after a stabilizing periodfollowing the cooled period.
 10. A system according to claim 1, whereinthe computer processor is further configured to execute the program codeto perform at least one of the steps to: estimate the heat gained insidethe building through the internal sources of heat as a function ofenergy consumed within the building from the beginning of the unheatedperiod through the end of the stabilizing period; and estimate the heatgained inside the building through the internal sources of heat as afunction of heat generated by occupants present in the building from thebeginning of the unheated period through the end of the stabilizingperiod.
 11. A method for empirical-test-based estimation of overallthermal performance of a building with the aid of a digital computer,comprising: providing a non-transitory computer readable storage mediumcomprising program code; providing a heating source comprising a heatingelement and a heating delivery component comprised inside a building;providing a thermometer comprised inside the building; providing athermometer located outside of the building; providing a computerprocessor interfaced to the storage medium and remotely interface, theheating source, the inside thermometer, and the outside thermometer,wherein the computer processor is configured to execute the programcode; stopping with the computer processor operation of the heatingsource at the beginning of an unheated period after recording into thestorage medium a baseline indoor temperature from the indoor thermometerand a baseline outdoor temperature from the outdoor thermometer;temporarily resuming with the computer processor operation of theheating source at the end of the unheated period after recording intothe storage medium a starting indoor temperature from the indoorthermometer; stopping with the computer processor operation of theheating source after running the heating source for a heated period andrecord into the storage medium a final indoor temperature from theindoor thermometer after a stabilizing period following the heatedperiod; measuring with the computer processor energy consumed in thebuilding from the beginning of the unheated period to the ending of thestabilizing period as equaling heat gained inside the building frominternal sources of heat; estimating with the computer processor anexpected final indoor temperature at the end of the stabilizing periodbased on the heating source not having been run for the heated period;determining with the computer processor the heat gained inside thebuilding over the heating period through operation of the heating sourceusing the fuel requirements of the heating source, the efficiency of theheating source, and the efficiency of the heating delivery component;estimating with the computer processor overall thermal performance ofthe building using the heat gained through using the heating source, themeasured energy, the indoor temperatures, the baseline outdoortemperature, and the estimated final indoor temperature.
 12. A methodaccording to claim 11, wherein the heat gained inside the building bythe heating source having been run for the heated period is determinedin accordance with:$Q^{{Heat}\mspace{14mu} {Delivered}\text{-}{Furnace}} = {\left( R^{Furnace} \right)\left( {\eta^{Furnace}\eta^{Delivery}} \right)\left( {t_{2} - t_{1}} \right)\left( \frac{T_{0} - T_{3}^{{No}\mspace{14mu} {Heat}}}{T_{3} - T_{3}^{{No}\mspace{14mu} {Heat}}} \right)}$where Q^(Heat Delivered-Furnace) is the heat gained inside the buildingby the heating source having been run for the heated period, R^(Furnace)are the fuel requirements of the heating source, η^(Furnace) is theefficiency of the heating source, η^(Delivery) is the efficiency of theheating delivery component, t₁ is the starting time of the heatedperiod, t₂ is the ending time of the heated period, T₀ is the baselineindoor temperature, T₃ is the final indoor temperature, T₃ ^(No Heater)is the expected final indoor temperature, Δt is the unheated period fromtime t₀ to time t₁.
 13. A method according to claim 11, wherein the fuelrequirements Q^(F-Heating) of the heating source is determined inaccordance with:$Q^{F\text{-}{Heating}} = \frac{\left( {UA}^{Total} \right)(24)\left( {HDD}_{Location}^{{Set}\mspace{14mu} {Point}\mspace{14mu} {Temp}} \right)\left( {1 - {SSF}} \right)}{\eta^{Furnace}\eta^{Delivery}}$where UA^(Total) is the building thermal performance, HDD_(Location)^(Set Point Temp) represents the number of degree days when the outdoortemperature exceeds the desired Set Point temperature, η^(Furnace) isthe efficiency of the heating source, η^(Delivery) is the efficiency ofthe heating delivery component, and SSF represents the amount of energydelivered to a building by solar gains.
 14. A method according to claim11, further comprising the steps of: using with the computer processorthe overall thermal performance of the building to analyze one or morepotential energy investments into the building, wherein at least one ofthe energy investments is performed based on the analysis.
 15. A methodaccording to claim 14, further comprising: measuring by a meterinterfaced to the computer processor data associated with the buildingand providing the data to the computer processor, wherein the computerprocessor further uses the provided data to evaluate the one or moreenergy investment for the building.
 16. A method according to claim 15,wherein the data comprises one or more of electricity consumptionassociated with the building, fuel consumption associated with thebuilding, and photovoltaic power generation data by a photovoltaic powergeneration plant interfaced to the building.
 17. A method according toclaim 11, further comprising the steps of: recording into the storagemedium the outdoor temperature at one or more additional time pointsfrom the outdoor thermometer between the beginning of the unheatedperiod and the end of the stabilizing period; and average the baselineoutdoor temperature and one or more of the outdoor temperatures taken atone or more of the additional time points, wherein the averaged outdoortemperature is used to estimate the overall thermal performance of thebuilding.
 18. A method according to claim 11, further comprising thesteps of: providing a cooling source that is comprised within thebuilding and that is interfaced to the computer processor; stopping withthe computer processor operation of the cooling source at the beginningof an uncooled period after recording into the storage medium a furtherbaseline indoor temperature from the indoor thermometer and a furtherbaseline outdoor temperature from the outdoor thermometer; temporarilyresuming with the computer processor operation of the cooling source atthe end of the uncooled period after recording into the storage medium afurther starting indoor temperature from the indoor thermometer; andstopping with the computer processor operation of the cooling sourceafter running the cooling source for a cooled period and record into thestorage medium a further final indoor temperature from the indoorthermometer after a stabilizing period following the cooled period. 19.A method according to claim 11, further comprising steps of: estimatingwith the computer processor the heat gained inside the building throughthe internal sources of heat as a function of energy consumed within thebuilding from the beginning of the unheated period through the end ofthe stabilizing period; and estimating with the computer processor theheat gained inside the building through the internal sources of heat asa function of heat generated by occupants present in the building fromthe beginning of the unheated period through the end of the stabilizingperiod.
 20. A non-transitory computer readable storage medium storingcode for executing on a computer system to perform the method accordingto claim 11.